Basic Basics on Robotica, Artificial Intelligence.

The general public met the word robotic through the work R.U.R.. (Rossum's Common Robots) by Czech playwright Karel-apek , which premiered in 1921. 2 The word was written as “robotnik”.
However, it wasn't this author Aapek who invented the word. In a brief written letter to the Oxford Dictionary editorial, attributes to his brother Josef the creation of the term. In an article published in the Czech journal Lidovénoviny in 1933, explained that he originally wanted to call them labo-i (from Latin labor, work). However, didn't like the word and asked his brother Josef for advice, who suggested “roboti”. The word robot literally means work hard and figuratively “hard work” in Czech and many Slavic languages Traditionally robot period the period of work that a servant should grant to his lord, usually 6 months of the year. Servitude was banned in 1848 in Bohemia , so when Aapek wrote R.U.R., the use of the term robot had already spread to various types of work, but the outdated meaning of “servitude” would continue to recognize each other.
The word robotics , used to describe this field of study, was coined by science fiction writer Isaac Asimov Robotics concentrates 6 areas of study: Mechanics, automatic management, electronics, computer science, and physics and mathematics as basic sciences.
The word robot was first used in 1921, when Czech writer KarelCapek (1890 – 1938) premieres at Prague National Theatre his work Rossum's Universal Robotic (R.U.R.). Its origin is of the Slavic word robot, which refers to the work done on a forced.
With the aim of designing a flexible machine, adaptable to the environment and easy to use, George Devol, pioneer of Industrial Robotics, patented in 1948, a programmable manipulator that was the germ of the industrial robot.
In 1948 R.C. ArgonneNationalLaboratory's Goertz development, in order to manipulate radioactive elements without risk to the operator, the first tele manipulator. This consisted of a master-slave mechanical device. The Master Manipulator, faithfully reproduced the movements of this. The operator in addition to being able to observe through a thick glass the result of his actions, felt through the master device, the forces that the slave exercised over the environment.
Years later, in 1954, Goertz made use of electronic technology and servo control by replacing mechanical transmission with electric and thus developing the first tele manipulator with bilateral servo control. Another pioneer of tele manipulation was Ralph Mosher, Basic Electric engineer who in 1958 developed a device called Useful-Man, consisting of two mechanical arms teleoperated by a master of the type called exoskeleton. Together with the nuclear industry, throughout the 1960s the underwater industry began to take an interest in the use of tele manipulators.
Added to this interest was the space industry in the 1970s.
The evolution of tele manipulators over the last few years has not been as spectacular as that of robots. Held in a select and limited market(nuclear industry, military, spatial, and many others.) are generally unknown and comparatively unreeded by the investigative- robot users and users. By its own conception, a tele manipulator requires the continuous control of an operator, and except for the contributions incorporated with the concept of supervised control and the improvement of the tele presence promoted today by digital reality, their abilities have not changed much from those of their origins.
Replacing the operator with a computer program that controlled the movements of the manipulator gave way to the concept of robotics.
The first patent for a robotic device was filed in March 1954 by British inventor C.W. Kenward. This patent was issued in the United Kingdom in 1957, however it was Geoge C. Devol, American engineer, inventor and author of several patents, he laid the foundations for modern industrial robotics. In 1954 Devol conceived the concept of a scheduled item transfer device that was patented in the United States in 1961.
In 1956 Joseph F. Engelberger, engineering director of Manning Maxwell and Moore's aerospace division at Stanford, Connecticut. Together Devol and Engelberger began working on the industrial use of their machines, founding the ConsolidatedControlsCorporation, that later becomes Unimation(Universal Automation), and installing his firstunimate machine (1960), at The General Motors factory in Trenton, New Jersey, in an injection casting application.
Other big companies like AMF, undertook the construction of similar machines (Versatran- 1963.
In 1968 J.F.. Engelberger visited Japan and soon after agreements were signed with Kawasaki for the construction of Unimate-type robots. Japan's robotics growth soon outpertches the United States thanks to Nissan, that formed the world's first robotics association, Japan Industrial Robotics Association (picnic) in 1972. Two years later, the Institute of Robotics of America was formed (ria), that in 1984 changed its name to the Association of Robotic Industries, keeping the same acronym (ria.
For its part Europe had a later awakening. In 1973 swedish firm ASEA built the first robot with all-electric drive, in 1980 the Stockholm Sweden-based International Robotics Federation was founded.
The configuration of the first robots responded to the so-called spherical and anthropomorphic configurations, especially useful for handling. In 1982, Professor Makino of Yamanashi University of Japan, develops the SCARA robot concept (SelectiveComplianceAssembly Robot Arm) looking for a robotic with a numberreduced in degrees of freedom (three four), limited cost and assembly-oriented configuration of parts.
The definition of industrial robotics, as a machine that can perform a diverse number of jobs, automatically, by pre-scheduling, it's not valid, because there are quite a few numerical control machines that meet those requirements. One peculiarity of robots is their mechanical arm structure and another their adaptability to different apprehensive tools. Another specific feature of the robot, is the possibility of carrying out completely different work and, even, making decisions based on information from the outside world, through the appropriate operating program on your computer system.
Five relevant phases can be distinguished in the development of Industrial Robotics:
1. The ARGONNE laboratory designs, in 1950, master-slave manipulators to handle radioactive materials.
2. Unimation, founded in 1958 by Engelberger and now absorbed by Whestinghouse, carries out the first robot projects in the early 1960s of our century, installing the first one in 1961 and then, in 1967, a set of them in a factory of general motors. Three years later, the implementation of robots in Europe begins, especially in the area of automobile manufacturing. Japan begins implementing this technology until 1968.
three. Stanford University and MIT Laboratories, in 1970, the task of controlling a robot by computer.
four. In 1975, the application of the microprocessor, transforms the image and characteristics of robotics, until then large and expensive.
5. Starting in 1980, the strong drive in research, by robot manufacturers, other assistants and various departments of universities around the world, applied computing and sensor experimentation, increasingly refined, enhance the smart robot configuration capable of adapting to the environment and making decisions in a current time, adapt them for each situation.
In this phase that lasts from 1975 to 1980, the combination of the effects of the Microelectronics revolution and the revitalization of automotive companies, produced a cumulative growth of the robot park, close to 25%.
The evolution of industrial robots since its beginnings has been dizzying. In just over 30 years, research and developments on industrial robotics have allowed robots to take positions in almost all productive areas and types of industry. In small large factories, robots can replace man in those repetitive and hostile areas, adapting immediately to the production changes requested by variable demand.
Robotics is a branch science of technology, that studies the design and construction of machines capable of performing tasks performed by humans that require the use of intelligence. The sciences and technologies from which it derives could be: algebra, programmable automatons, state-of-the-state machines, computer mechanics.
Robotics is the branch of technology that is dedicated to the design, construction, operation, structural disposition, manufacturing and application of robots Robotics combines various disciplines such as: mechanics , electronics , computer science , artificial intelligence , control engineering and physics Other important areas in robotics are algebra , programmable automatons and state machines
Robotics is the science and technique that is involved in design, the manufacture and use of robots A robotic is, on the other hand, a machine that can be programmed to interact with objects and get it to imitate, in a way, animal human behavior.
Human beings since their inception have sought a way to adapt and change their lifestyle, from the most difficult conditions has emerged how to facilitate the condition of human life, to improve their quality and to facilitate productive ways of jobs that reduce man's physical effort in his daily tasks. Robotics, as outlined is the science that studies the design and construction of smart machines, it is a set of theoretical and practical knowledge that allow to develop the thought of performing and automating systems based on poly articulated structures. These machines are manufactured with some intellectual capacity and are intended for industrial production to replace the real participation of human beings in certain tasks. Impressively robotic systems are able to receive information and understand their functions and execute them accurately.
Nothing comes out of nowhere, questions arise to understand this revolutionary concept that has arisen in the life of the human being. To understand this advancement of science and high technology, it is necessary to go back to its origins. The term Robot, it's a Czechoslovak word whose meaning is 'servant worker', emerged with carel Capee's Universal Rossum Redbots. From ancient Greek times an attempt was made to create devices that had endless movement and that did not have to be controlled by people. By the 17th and 18th centuries Jacques de Vaucanson, built the so-called humanoid automatons manufactured with watchmaking mechanisms. Continued developments between debates, uncertainty and constant efforts.
In science fiction the three laws of robotics are a set of rules written by Isaac Asimov , that most of the robots in his novels and short stories are designed to meet. In that universe, laws are “mathematical formulations printed on the positronic paths of the brain” of robots (lines of code of the robotics operating program stored in the robotics' ROM). First featured in runaround ( 1942 ), establish the following:
1. A robotic can't hurt a human being , by inaction, allow a human being to suffer harm.
2. A robotic must obey the orders given by humans, unless these orders conflicted with the First Law.
three. A robot must protect its own existence to the extent that this protection does not conflict with the First Law. 1
This wording of laws is the conventional way in which humans in stories enunciating them; its real form would be that of a series of equivalent and much more complex instructions in the robotics' brain.
Asimov attributes the three Laws to John W. Campbell , who would have drafted them during a sustained conversation on December 23, 1940 However, Campbell argues that Asimov already had them in mind, and who simply expressed them between the two in a more formal way.
The three laws appear in a large number of Asimov stories, as they appear throughout their series of robots, as well as in several related stories, and the series of novels starring LuckyStarr have also been used by other authors when they have worked on Asimov's fictional universe, and references to them in other works are frequent, both sci-fi and other genres.
Today, commercial and industrial robots are widely used, and perform tasks more accurately cheaper than humans. They are also used in overly dirty jobs, dangerous tedious to humans. Robots are widely used in manufacturing plants, assembly and packaging, in transport, in explorations on Earth and in space, surgery, armament, research in laboratories and in the mass production of consumer industrial goods.
Other applications include cleaning toxic waste, mining, search and rescue of people and location of landmines.
There is great hope, especially in Japan , that home care for the elderly can be performed by robots.
Robots seem to be shrinking and reducing their size, a trend related to miniaturization of electronic components that are used to control them. In addition, many robots are designed in simulators long before they are built and interact with real physical environments. A good example of this is the Spiritual Machine team, 12 a team of 5 robots fully developed in a virtual environment to play football in the F.I.R.A. World League.
In addition to the fields mentioned, there are models working in the education sector, services (for example, instead of human receptionists 14 surveillance) and search and rescue tasks.
Today, commercial and industrial robots are widely used, and perform tasks more accurately cheaper than humans. They are also used in overly dirty jobs, dangerous tedious to humans. Robots are widely used in manufacturing plants, assembly and packaging, in transport, in explorations on Earth and in space, surgery, armament, research in laboratories and in the mass production of consumer industrial goods.
Other applications include cleaning toxic waste, mining, search and rescue of people and location of landmines.
There is great hope, especially in JAPAN, that home care for the elderly can be performed by robots.
Robots seem to be shrinking and reducing their size, a trend related to miniaturization of electronic components that are used to control them. In addition, many robots are designed instimulators long before they are built and interact with real physical environments. A good example of this is the Non secular Machine team, a team of 5 robots fully developed in a virtual environment to play football in the world league
In addition to the fields mentioned, there are models working in the education sector, services (for example, instead of human receptionists surveillance) and search and rescue tasks.
The following is the most common classification:
1st Generation.
2nd Generation.
Learning robots. Repeat a sequence of movements that has previously been executed by a human operator. The way to do this is through a mechanical device. The operator performs the required movements while the robot follows and memorizes them.
3rd Generation.
Robots with sensorized control. The controller is a computer that executes the orders of a program and sends them to the manipulator to make the necessary movements.
4th Generation.
Smart robots. They are similar to the previous ones, but they also have sensors that send information to the management computer about the state of the process. This enables intelligent decision-making and control of the process in a current time.
The word cybernetics comes from greek Κυβερνήτης (kybernetes) and it means “art of piloting a ship”, although Plato used it in The Republic with the meaning of “art of directing men” “art of governing”. This is an old generic term but still used for many areas that are increasing their specialization under titles such as: adaptive systems, artificial intelligence, complex systems, complexity theory, control systems, organizational learning, theory of mathematical systems, decision support systems, system dynamics, information theory, operations investigation, Simulation and Systems Engineering.
A robotic , is a digital mechanical artificial agent It is a machine used to perform a job automatically and that is controlled by a computerI'm well the word robotic can be used for physical agents and virtual agents of software program , the latter are called ” Bots ” to differentiate them from the others.
A robot is a programmable machine that can manipulate objects and perform operations that previously could only be performed by humans. Robotics can be both a physical electromechanical mechanism and a virtual software system. Both agree to provide the feeling of having the ability to think resolve, although they are actually limited to executing orders issued by people.
A robot is an artificial mechanical virtual entity. In practice, this is usually an electromechanical system that, because of his appearance his movements, offers the feeling of having a purpose of its own. The independence created in their movements makes their actions the reason for a reasonable and in-depth study in the area of science and technology. The word robotic may refer to both physical mechanisms and virtual software program systems, although it's often alluded to in seconds with the term bots.
1.- Robots Play-back, which regenerate a sequence of recorded instructions, like a robot used in arc welding spray coating. These robots commonly have open loop management.
2.- Sensor-controlled robots, these have a closed loop management of manipulated movements, and make decisions based on data obtained by sensors.
3.- Vision-controlled robots, where robots can manipulate an object by using information from a vision system.
4.- Adaptively controlled robots, where robots can automatically reschedule their actions based on data obtained by sensors.
5.- Robots with artificial intelligence, where robots use artificial intelligence techniques to make their own decisions and solve problems.
6.- Medical robotssson,fundamentally,prosthetics for decreased physicals that adapt to the body and are equipped with powerful command systems. With them it is possible to precisely match the movements and functions of the limb organs that supplement the body.
7.- Androids are robots that look alike and act like human beings. Today's robots come in all shapes and sizes, but with the exception of those that appear at fairs and shows, don't look like people and therefore they're not androids. currently, real androids only exist in imagination and in fictional films.
eight.- Mobile robots.- They are equipped with legs, wheels or tracks that enable them to move according to their schedule. They produce the information they receive through their own sensor systems and are used in certain types of industrial installations, especially for the transport of goods in production chains and warehouses. Robots of this type are also used for research in places that are difficult to access very distantly, as is the case of space exploration and investigations or underwater rescues.
Androids are robots that look alike and act like human beings. Today's robots come in all shapes and sizes, but with the exception of those that appear at fairs and shows, don't look like people and therefore they're not androids. currently, real androids only exist in imagination and in fictional films.
Mobile robots are equipped with legs, wheels or tracks that enable them to move according to their schedule. They produce the information they receive through their own sensor systems and are used in certain types of industrial installations, especially for the transport of goods in production chains and warehouses. Such robots are also used for research in hard-to-reach places very distant, as is the case with space exploration and underwater rescue investigations.
Robots characterized mainly by their locomotion system that mimics various living things. Androids could also be considered zoomomorphic robots.
Medical robots are, fundamentally, prosthetics for physical decreased that adapt to the body and are equipped with powerful command systems. With them it is possible to accurately match the movements and functions of the limb organs that supplement.
Industrial robots are mechanical and electronic contraptions intended to automatically perform certain handling manufacturing processes. They are currently the most frequent. Japan and the United States lead the manufacture and consumption of industrial robots with Japan being number one.
There are many “relatives of robots” that don't exactly fit the precise definition. An example is teleoperators. Depending on how a robot is defined, teleoperators may not be classified as robots. Teleoperators are remotely controlled by a human operator. When they can be considered robots they are called “telerobots”. Whatever your class, teleoperators are generally very sophisticated and extremely useful in hazardous environments such as chemical waste and pump deactivation. Teleoperative robots are defined by NASA as:Robotic devices with manipulative arms and sensors with a certain degree of mobility, remotely controlled by a human operator directly through a computer.
These robots correspond to those of difficult classification whose structure results from a combination of those set out above.
It should be said that although the above classification is the best known, there is another not least where you take more into account the power of the software program in the controller, which is decisive for the usefulness and flexibility of robotics within the limits of mechanical design and sensor capacity.
According to this position the robots have been classified according to:
– your generation
– level of programming language.
These ratings reflect the power of the software in the controller, in explicit, sophisticated sensor interaction. The generation of a robotic is determined by the historical order of developments in robotics. Five generations are normally assigned to industrial robots. The third generation is used in the industry, the fourth is developed in research laboratories, and the fifth generation is in research.
Human beings since their inception have sought ways to adapt and change their lifestyle, from the most difficult conditions has emerged how to facilitate the condition of human life, to improve their quality and to facilitate productive ways of jobs that reduce man's physical effort in his daily tasks. Robotics, as outlined is the science that studies the design and construction of smart machines, is a set of theoretical and practical knowledge that allow to develop the idea of performing and automating systems based on poly-articulated structures. These machines are manufactured with some intellectual capacity and are intended for industrial production to replace the real participation of human beings in certain tasks. Impressively robotic systems are able to receive information and understand their functions and execute them accurately.
Nothing comes out of nowhere, questions arise to understand this revolutionary concept that has arisen in the life of the human being. To understand this advancement of science and high technology, it is necessary to go back to its origins. The term Robot, it's a Czechoslovak word whose meaning is 'servant worker', emerged with carel Capee's Universal Rossum Redbots. From ancient Greek times an attempt was made to create devices that had endless movement and that did not have to be controlled by people. By the 17th and 18th centuries Jacques de Vaucanson, built the so-called humanoid automatons manufactured with watchmaking mechanisms. Developments continue between debates, uncertainty and constant effort to achieve what later became known as artificial intelligence.
Perform a task according to a series of pre-scheduled instructions, they execute sequentially. This type of robots has open loop control systems, so they don't take into account any variations that may occur in their environment.
This type does take into account variations in the environment. They have management systems in closed loop, sensors that allow them to acquire information about the environment in which they are located and adapt their actions to them.
They have capacity for automatic task planning; are robots adaptable to different environments, able to reschedule automatically, based on the data provided by the sensors.
research currently carried out on robotics is aimed at the development of the fourth generation of robots, that points to the creation of systems capable of making decisions and solving problems for themselves. It's what's been called artificial intelligence.
October 27 to November 3, 2010, Kuka Robots presents at Ok 2010 Quantec, a new generation of robots. With an extensive range of fifteen standard robots with various mounting options, Quantec series ensures that there is the right robotics for each specific application and customer. For the first time, a single family of robots completely covers ninety to 300 kg payload models with ranges of 2,500 to 3.a hundred mm. Automation is facilitated through maximum flexibility to system planning and design phase, reducing design and design work and better safety planning.
Quantec series robots, by Kuka, are characterized by having a hundred and sixty kg less weight and 25% less volume, maintaining the same range and payload. They are the most compact in their class, reducing space needs and opening up new fields for potential applications, even in restricted spaces. They even allow the design of compact cells in the high payload range.
Lighter quantec series components enable higher performance, and even shorter cycle times, as well as greater rigidity. The new robot series impresses with a great repeatability of precision and posture of + /- 0,06 mm.
Quantec series robots continue to be characterized by the customary quality and robustness of Kuka products. The series has been designed based on a concept of common parts, with only four engine and gear variants. All models have the same pattern for base mounting, the same as the previous series, and an identical flange on the wrist. This is why the Quantec series is a hundred% suitable with existing cell designs based on the 2000 series. The design of the series has minimized disruptive contours, and your compact wrist offers better accessibility even in restricted spaces.
Kuka actively follows a three-spear approach to environmental protection: in internal processes within the company itself, in your product portfolio, and in the intelligent automation of competitive production sequence of green technologies, as solar cells vehicles that use new, more environmentally friendly energy sources.
The company has set a goal, as far as possible, sustainable production with the least possible impact on the natural resources of our planet. A practical example: KUKA is the world's first robot manufacturer to use eco-friendly and nautical paint for its robot systems. Annual energy savings averaging 8% per robotic manufactured have been achieved in production over the past five years. The photo voltaic cell on the roofs of the plant provides electricity.
With the KR C4, another of the novelties of the salon, Kuka launches a control system that integrates robot, movement, control of sequences and processes. But that's not all.. Even more important is the fact that the full safety controller is seamlessly integrated into the KR C4's management system.. That is to say, kr c4 performs all tasks immediately.
In the new control system, Kuka has dispensed with restrictive hardware and replaced it with intelligent software features. Therefore, the concept is characterized by its absolute transparency and future compatibility. Conventional interfaces are replaced by bound data flow, thus allowing direct communication between the individual control modules of the KR C4.
The KR C4 concept provides a firm foundation for future automation. The systematic removal of limited hardware and its replacement with commonly used elements, industry standards, as 'multi-core’ and Ethernet technology, offer enormous potential in development and performance. Based on these technologies, Ethernet-based bus systems, as ProfiNet Ethernet/IP, can be easily integrated as software program functions. In this way, the KR C4 concept will automatically benefit future advances in development and performance. This new approach, applying management processes as software program functions, reduces the number of hardware modules by 35% and connectors and cables by 50%.
For the first time, the full security control is seamlessly integrated into the KR C4's control system without its own hardware. Security and communications features are applied on the basis of Ethernet-based protocols.
The concept of security in the KR C4 focuses on the use of multi-core technology", this ensures the dual-channel system needed for security applications. In addition, the system offers much more than just monitoring of functions. In fact, this concept makes it possible to influence the movement and speed of the robot safely. The elimination of hardware limiting components and the unlimited expandability of software-based security interfaces paves the way for the application of revolutionary new security concepts in automation. Especially in the field of cooperation between human and robot, where new sensors will be used in the future. Which in any case will require many inputs and outputs. Kr C4 architecture gives KukaRoboterGmbH the flexibility to integrate them.
Robots have three characteristics that are their own:
– planning
– learning.
The capture of sensory information is basic above all the recognition of forms or objects, which has given a great boom to research on computer vision. Many of the tasks they perform involve a high level of complexity and decision-making, activities that an automaton cannot perform, since they involve considered principles of action “Smart” so this area has become one of the most important in AI (Artificial intelligence).
On the other hand, if we compare robots with humans we can distinguish the following characteristics:
-Robots can be stronger, allowing them to lift considerable weights and apply greater forces.
-They do not get tired and can easily work 24 hours a day. of the day and 7 days of the week. They don't need breaks and rarely get sick.
-They are consistent. Once they have been instructed to perform a job they can repeat it, virtually indefinitely, with a high degree of accuracy. Human performance tends to deteriorate over time.
-They are almost completely immune to their environment. They can work in extremely cold hot environments, in areas where there is a danger of toxic gases radiation.
-They handle objects with very high temperatures. They are able to work in the dark.
Various researches among industrial users show the industry's reasons for the incorporation of robots
The list of priorities for Japanese industry is as follows:
-labour saving
-improvement of working conditions-greater flexibility
-ease of production control
A study in German industry resulted in the following list of priorities:
– increased productivity
– return on investment-quality improvement
-more humane working conditions
A robotic is formed by the following elements: mechanical structure, transmissions, Actuators, sensors, terminal and controller elements. Although the elements used in robots are not exclusive to them (machine tools and many other machines employ similar technologies), the high performance required of robots has led to the use of elements with specific characteristics.
The physical constitution of most industrial robots bears some similarity to the anatomy of the upper extremities of the human body, so, sometimes, to refer to the different elements that make up the robot, terms such as waistline are used, shoulder, arm, elbow, wrist, and so forth.
The main components of a robotic are as follows::
Mechanically, is the main component. It consists of a series of solid structural elements linked by joints that allow a relative movement between each two consecutive links. The parts that make up the manipulator receive, among others, the names of: body, arm, wrist and final actuator ( terminal element). The latter is commonly referred to as an apprehensor, claw, gripper clamp.
The most common are: keyboard, monitor and command box (teachpendant). Input and output devices allow you to enter and, in turn, viewing driver data. To send instructions to the controller and to register control programs, an additional computer is commonly used. It is necessary to clarify that some robots only have one of these components. In these cases, one of the input and output components allows the performance of all functions.
Among these are the axes that facilitate the transverse movement of the manipulator and the assembly stations, which are used to hold the different pieces of work.
There are different types and classes of robots, among them in human form, of animals, of plants even of architectural elements but all are differentiated by their capacities and are classified into 4 forms:
1. Androids
Robots in human form. They mimic people's behavior, its usefulness today is experimentation-only. The main limitation of this model is the implementation of balance in displacement, as it is bipedal.
2. Mobile
They move by means of a rolling platform (wheels); these robots ensure the transport of parts from one point to another.
It is a locomotion system imitating animals. The application of these robots serves, above all, for the study of volcanoes and space exploration.
They move their limbs with few degrees of freedom Their main utility is industrial , to move items that require care.
In short, a robotic has evolved as a replica of its creators, bridging distances. The whole bears some similarity to our own body.
Hands and arms are reflected in the mechanical parts: the manipulator and the tool. The muscles would be the actuators and the nerve endings, regulators.
The brain (driver equivalent) is in charge of sending orders to the muscles through the nerve endings and receiving information through the senses (sensors).
At last, the way of thinking and acting would be determined by the control software resident on the computer.
Ability to reason of a non-living agent. John McCarthy, coined the term in 1956, defined it: “It's the science and engineering of making intelligent machines, especially intelligent computer programs.”To explain the above definition, understand an intelligent agent that allows you to think, evaluate and act according to certain principles of optimization and consistency, to satisfy some purpose purpose. According to the previous concept, rationality is more basic and therefore more appropriate than intelligence to define the nature of the objective of this discipline.
It is a combination of computer science, physiology and philosophy, as normal and broad as that, is that it brings together several fields (robotics, expert systems, for example), which have in common the creation of machines that can think. The thought of building a machine that can execute tasks perceived as requirements of human intelligence is an attraction. Tasks that have been studied from this point of view include games, language translation, language comprehension, fault diagnosis, robotics, provision of expert advice on various topics.
Intelligence is linked to knowing how to choose the best options to solve some type of problem. There are different types of intelligence according to their attributes and processes, as operational intelligence, biological intelligence psychological intelligence. artificial, on the other hand, is an adjective that indicates that made by hand, art wit of man. The artificial also allows to name the unnatural false. The notion of artificial intelligence was developed in reference to certain systems created by humans that constitute non-living rational agents
The history of Artificial Intelligence has gone through various situations:
•The term was invented in 1956, at the Dartmouth Conference , a congress in which triumphalist ten-year forecasts were made that were never fulfilled, which led to the almost complete abandonment of research for fifteen years.
• In 1980 history repeated itself with the Japanese challenge of the fifth generation of computers, which led to the rise of expert systems but did not achieve many of its objectives, so this field suffered a new interruption in the nineties.
•Today we are as far from fulfilling the famous Turing test as when it was formulated: Artificial Intelligence will exist when we are not able to distinguish between a human being and a computer program in a blind conversation.
•As an anecdote, many of the AI researchers argue that “intelligence is a program capable of being executed regardless of the machine that executes it, brain computer”.
Ancient mathematical games, as that of theTorres of Hanoi (about 3000 BC.C.), demonstrate interest in finding a resolving loop, an AI capable of winning in the minimum possible moves.
In 1903 Lee De Forest invented the triode , also called vacuum valve bulb Arguably the first great man-made intelligent machine was the ENIAC computer, composed of 18.000 vacuum valves, taking into account that the concept of “intelligence” it is a subjective term that depends on the intelligence and technology that we have at that time.
In 1937 Turing published an article of considerable impact on the “Calculable Numbers”, which can be considered the official origin of theoretical computer science.
In this article he introduced the concept of Turing machine , an abstract mathematical entity that formalized the concept dealgoritmo and proved to be the forerunner of digital computers. With the help of your machine, Turing was able to show that there are unsolvable problems, from which no computer will be able to obtain its solution, so he is considered the father of computability theory He is also considered the father of Artificial Intelligence for his famous Turing Test , which would make it possible to check whether a computer program can be as intelligent as a human being.
In 1951 William Shockley invented the junction transistor. The invention made possible a new generation of much faster and smaller computers.
In 1956 the term was coined “artificial intelligence” in Dartmouth during a conference convened by McCarthy, which they attended, among others, Minsky ,Newell and Simon At this conference, triumphalist ten-year forecasts were made that were never fulfilled., which led to the almost complete abandonment of research for fifteen years.
In 1980 history repeated itself with the Japanese challenge of the fifth generation, which led to the rise of expert systems but did not achieve many of its objectives, so this field suffered a new interruption in the nineties.
In 1987 Martin Fischles and Oscar Firschein described the attributes of an intelligent agent. When trying to describe with a wider scope (not just communication) the attributes of an intelligent agent, AI has expanded into many areas that have created huge and differentiated branches of research. These attributes of the intelligent agent are:
1.You have mental attitudes such as beliefs and intentions.
2.You have the ability to gain knowledge, I mean, learn.
three. Can solve problems, even partitioning complex problems into simpler ones.
4.Understand. It has the ability to make sense of it, if possible, to contradictory ambiguous ideas.
5.Plan, predicts consequences, evaluate alternatives (as in chess games)
6.Know the limits of your own skills and knowledge.
7. Can distinguish despite the similarity of the situations.
8.Can be unique, even creating new concepts ideas, and even using analogies.
9.You can generalize.
eleven. You can understand and use language and its symbols.
We can then say that AI includes human characteristics such as learning, adaptation, reasoning, autocorrect, implicit improvement, and the modular perception of the world. Like this, we can no longer talk about just one goal, but of many, depending on the utility point of view that may be found to the AI.
Many of the AI researchers argue that “intelligence is a program capable of being executed regardless of the machine that executes it, brain computer”.
“Develop an intelligent machine capable of learning through experience, recognize the limitations of your knowledge, exhibit true creativity, make her own decisions and interact with the environment around her”
“Make computers capable of displaying behavior that is considered intelligent by a human observer (Turing test)”.
“Raise the IQ of machines (machine-IQ)”
“Develop the capabilities of the computer beyond its precise traditional use”.
Early research on artificial intelligence was mainly aimed at finding a common technique for problem solving.. This large-scale attempt has been abandoned and current research is aimed at the design of numerous computer programs capable of mimicking expert decision-making processes., as doctors, chemists, based on the knowledge of specialists in each subject, are now used to diagnose diseases, identify chemical molecules, locate mineral deposits and even design manufacturing systems. Research on perception has been applied to robots and some capable of “see”. The ultimate goal is to create a system capable of reproducing all facets of human intelligence..
Computers are fundamental today in our lives affecting all aspects of this. Artificial Intelligence is created with the implementation in computers to perform computing mechanism that uses fixed programs and contains a series of rules that make it work.
This allows computers to be created on artificial machines that perform monotonous tasks, repetitive and simple more efficient and effective than a human being. Studies on repetitive work tasks have shown that the human being does not like this type of work and as time passes they are more susceptible to making mistakes in it. For complex situations the goal becomes more complex because the artificial intelligent given to computers has difficulty understanding certain specific problem situations and how to react to these. It also happens that within a problem they have the variability of it and can not adapt to a change that may occur.
These problems are of utmost importance for Artificial Intelligence that seeks to improve, learn, understanding and reasoning for computer behavior in complex situations. The field of Artificial Intelligence science is still in stages of growth compared to other branches of computers but little by little the study of human behavior will give way to apply this knowledge to computers and these achieve in a primitive way reasons about different situations.
The complexity in applying human knowledge to computers is the ability of computers to be unpredictable and the different ways in which they act in a possible situation and these reactions make it difficult to implement a pattern within the memory of a computer.. So far there is no possibility of predicting to store all kinds of behavior of a human being to all the situations that it faces during its existence.
The purpose of artificial intelligence is to create theories and models that show the organization and functioning of intelligence. currently, the greatest effort in the search for artificial intelligence is focused on the development of data processing systems that are capable of imitating human intelligence, performing tasks that require learning, troubleshooting and decisions. Sometimes called machine intelligence, artificial intelligence AI (Artificial Intelligence) covers a wide range of theories and practices.
The purpose of machines and computers to mimic human abilities such as: object recognition, colors distances, in other cases imitate affective reactions and represent them through gestures.
Following this line of research have been designed systems such as Deep Blue, chess program, implemented on an IBM in 1996, which had an artificial intelligence algorithm. To test the system, the world chess champion was invited, Kasparov, to compete withDeep Blue. The victory corresponded to the human being. The following year, he was invited back and was defeated by Deep Blue, because the system had learned its own techniques. In other words, Kasparov had played against himself.
As well as this project, engineers and scientists around the world are conducting countless investigations whose purposes range from reproducing insect behaviors to imitating the mind of man himself. The applications for these systems are diverse.
For example, may have an industrial use: adapted to industrial machines, these achieve a productivity greater than that of a human being; as they perform, with greater speed and without making mistakes, the same tasks that a worker performs. However, these systems can also be used for destructive purposes, as is the case with weapons of war.
Artificial intelligence, commonly abbreviated as AI, is a part of technology and science that is responsible for designing robotic systems that can make decisions; I mean, that show a certain type of robotic intelligence to solve certain types of problems. While there is still a long way to go to develop thinking machines, great progress has been made in this regard in recent years., but how did the development of artificial intelligence come about??
To know the origins of artificial intelligence we have to go back to 1943, when the mathematician Walter Pitts and the neurophysiologist Warren McCulloch presented the first research paper where they talked about AI and where they mentioned concepts of basic human physiology, the way neurons work in our brains and Alan Turing's computational theory, among other things.
The importance of the work presented by Pitts and McCulloch focuses on the fact that it was the first work in history focused on AI., in addition, the analysis of the human brain that they did involves understanding it as if it were a computational organism., and finally, proposed the construction of computers similar to the biological neural networks of the human brain. It is in this way that the greatest contribution of Pitts and McCulloch to the development of artificial intelligence was that they founded the foundations of artificial neural networks..
Thirteen years later, back in 1958, an engineer named Josehp Engelberger designed and built the first industrial robotic in history, known as Unimate, reason why he was awarded the title of father of robotics. However, according to Engelberger himself, what inspired him to build his robotics were the science fiction stories written by Russian biochemist and writer Isaac Asimov.
That's right, science fiction throughout its history has been right to many of the future developments, although he has certainly also failed in some of his ideas; the truth is that Asimoves one of those authors that we could consider a visionary, because much of what he has written in his works has been fulfilled, especially that involves robots and robotics.
It was in 1942 that Asimov published his book Runaround, in which he expressed for the first time his now famous Laws of Robotics, with which robots were forced to stay under the orders of humans.
Applicability to poorly structured data and problems, without Artificial Intelligence techniques programs can not work with this type of problems. An example is conflict resolution in goal-oriented tasks such as in planning, diagnosing tasks in a system in today's world: with little information, with a close and not necessarily exact solution.
Expert systems, that reproduce human behavior in a narrow field of knowledge, are programs as varied as those that diagnose blood infections and indicate treatment, those that interpret seismological data in geological exploration and those that configure complex high-tech equipment.
Such tasks reduce costs, reduce risks in human handling in hazardous areas, improve the performance of inexperienced staff, and improve quality control especially in the commercial field.
The above definitions imply that machines to be considered intelligent must exhibit certain abilities, complex enough to be treated as separate areas. The way of approaching each of these areas is usually so dissimilar, that it is difficult to recognize a common origin.
1- Natural Language Processing
three- robotics
8- Perception and recognition of patterns
9- Self-learning
Representation of knowledge in data structures
Exploring state space:
Look for solutions to modernized problems with graphs
With the help of a human expert
The areas of application of Artificial Intelligence can be divided into two, according to the content of the study according to the tools and techniques used. They are developed below.
Since humans and other animals, and also intelligent robots and other artifacts, have a wide variety of capabilities, all of them very complex and difficult to explain modeling, both scientifically and engineeringly, AI has generated several subfields, dealing with particular aspects of intelligence.
(B) Techniques
Because the applications of AI are many and varied, some of the subfields are grouped around techniques relevant to each class of problems.
Perception, especially vision, but also auditory and tactile perception, and, most recently, taste and smell. This is broken down into the study of the different types of processes including physical transduction, pattern analysis and recognition, segmentation and “parsing” sensory data complex, Interpretation and care management. This is a huge subfield and can be divided into more specialized fields according to the sensory modality, the kinds of things that are perceived, The forms of representation used, If perception is purely data-driven, it includes prime-down processes, The mechanisms used (e.g. symbolic neural), The Largest Architecture Containing the Sensory System, and the application domain.
Natural Language Processing, including the production and interpretation of spoken and written language, whether handwritten, Electronic Print Throughout (e.g. email).
Learning & Development, including symbolic learning processes (For example, the induction rule), The use of neural networks (sometimes described as sub-symbolic), the use of evolutionary algorithms, Self-purification systems, and various types of self-organization.
Planning, Troubleshooting, Automatic design: given a complex problem and a collection of resources, Constraints and Evaluation Criteria Create a solution that meets the constraints and does so well is optimal according to the established criteria, If this is not possible, it is possible to propose some good alternatives.
Variety of reasoning: This includes the study of both common-sense casual reasoning and specialized expert reasoning. The first 2 includes the study of analogical reasoning, Inference with reversal, Case-Based Reasoning. The latter includes logic and mathematical reasoning, including the design of theorem proofers and inference systems, either with the intention of modeling various kinds of human inferential and mathematical abilities, For Practical Purposes, for example, in symbolic algebra toolkits", Reasoning in Robots, Autonomous Management Systems.
Study of representations: Investigating the formal properties of different types of representations, the mechanisms necessary for its operation, and the kind of tasks they're good at and bad at. This may include the study of ontologies of various types. Some mechanisms are sometimes said to use no representation at all (e.g. Neural networks), whereas they really are a special kind of representation, for example, numerical and continuous, as opposed to the structural and discrete.
Memory Techniques and Mechanisms: Analysis of the needs of the various types of memory, including large stores of knowledge containing various types of, whether to model human knowledge for use in various types of applications.
Multi-Agent Systems: the study of the various types of communication (linguistic and non-linguistic, explicit and implicit, intentional and unintentional), Types of Cooperation and Conflict, acknowledging the plans and intentions of others, and many others. Some studies of multi-agent systems have to do with understanding human social interactions, while others are concerned with designing applications that involve multiple robots, multiple systems, concurrent software. Some multi-agent systems are proposed as an architecture for a single complex intelligent agent.
Affective mechanisms: During the 1990s there has been a growing interest in the role of motivation and emotions in intelligence. This is sometimes studied as a topic of its own, and, Sometimes, as part of the study of complete architectures for intelligent autonomous systems. A normal theory would have to represent a wide variety of affective states and processes, including wishes, Preferences, Antipathies, Pleasures, Pains, Long-term goals, Intentions, Ideals, values, attitudes, Moods, and much more. One of the current debates concerns whether emotions are necessary for intelligence, if they are simply side effects, new features of mechanisms that are required for other functions.
robotics: one of the oldest sub-fields of AI. Sometimes studied for the purpose of producing new types of useful machines, and, Sometimes, because fully designing working robots provides a test bed for the integration of theories and techniques from different subfields of AI, for example, perception, learning, memory, Motor control, planning, and so forth. That is to say, It is a context for exploring concepts about complete systems. Sometimes, Robot designers try to show that certain types of mechanisms are not necessary in systems with a certain kind of intelligence, for example, showing what robots that don't use deliberation planning capabilities can do.
Language and tool development.
Complete System Architectures. Until the mid-1980s, most of the work in AI concerned specific forms of representation and specific algorithms to perform some task. Since, Increasing importance has been given to architecture in which many different mechanisms are combined to provide a system with many different types of functionalities, often simultaneously active mechanisms.
Search is another topic that should have been mentioned earlier, The search for a solution to a problem in a space of possibilities is a recurring theme in AI. Many different forms of search have been studied, in relation to the different forms of representation, Different Problem Domains and Different Requirements (for example, Should it be the optimal solution?, The goal is satisfactory? If it is not satisfactory enough, And it's very difficult to achieve the optimum, Can it be enough to find a solution that is guaranteed to be close to optimal?, within a certain limit?)
Ontologies have received appreciable attention after it has been shown that it is not enough to specify the forms of representation that an intelligent system uses. It's also important to research what kinds of things should be represented. An ontology specification is a specification of what kinds of things have to exist: Two people who share an ontology can, nevertheless, disagree as to what things that actually exist ontology could be allowed, What the Laws Govern Their Behavior. (This theme is closely linked to the old philosophical theories about what exists, what can exist.) The development of an ontology as a result of interaction with some environment is an important kind of learning. The above is not intended to be a complete list. There are many other child fields that could be listed.
There is a very open set of AI application fields. The following are just examples, and not a complete list:
AI in Education: It includes various types of smart tutoring systems and student management systems. Particular applications include diagnosing gaps in student knowledge, Various types of exercise and practice tutors, Automatic Dialing of Programming Exercises, and so forth.
AI in Mathematics: Designing tools to help with different kinds of mathematical functions, now so widely used that they are no longer recognized as products of AI.
AI in the Entertainment Industry: AI is increasingly being used in computer games, management and synthetic character generation systems, whether in the interaction through text with the generation of films with animated "interactive avatars" in virtual worlds.
AI in Biology: There are many complicated problems in biology where more less intelligent computer systems are being developed, for example, DNA analysis, Prediction of the folding structure of complex molecules, The Prediction, modelling of biological processes, evolution, Embryo development, Behaviour of different organisms.
AI in Law: for example, Expert Systems to Help Lawyers, systems for providing legal advice and assistance to non-lawyers.
AI in Architecture, Urban design, Traffic management: Tools to help solve design problems that present multiple constraints, Help predict people's behavior in new environments, tools to analyze the patterns of observed phenomena. On the Internet and other modern communication technologies, A graphical representation is called an avatar, Generally Human, that is associated with a user for identification. Avatars can be photographs, artistic drawings, and some technologies allow the use of three-dimensional representations.
AI in the literature, Art and music: Identification of the authors, modelling of generation processes and recognition, Teaching Apps.
AI in Crime Detection and Prevention: for example, Counterfeit Detection, Learning to Spot Signs of Police Corruption, software program to control transactions on the Web, Help plan police operations, Searching police databases for evidence that the crimes are committed by the same person, etc.
AI in Commerce: The Web has allowed commerce to be one of the fastest growing areas in terms of the number of applications developed, especially e-commerce and the use of software agents of various kinds to provide, To find, Analyze and interpret information, Making Decisions, Negotiate with other agents, and so forth.
AI in space: Remote management of spacecraft and autonomous robots.
AI in Military Activities: This may be the area where most of the funds have been spent and where it is not easy to learn from the details.
There are several of them, and they are:
Natural Language Processing:
Expert Systems:
Systems that are implemented experience to achieve deductions close to reality.
Mobile Robot Navigation, Mobile Arm Control, Assembly of parts, and so forth.
Perceptual Problems:
Vision and Speech, Speech recognition, Obtaining failures through vision, Medical Diagnostics, and so on.
But Artificial Intelligence also has numerous commercial applications in today's world. See:
Selection of the distribution of the components of a computer system.
Interpretation and analysis:
Equipment, Process Monitoring, Manufacturing & Scientific Process Management, Military Threats, Vital Functions of Inpatients, Financial Data in Teleprinter Perforated Paper Strips, Industry & Government Reports.
Asset and Liability Management, Portfolio Management, Credit & Loan Analysis, contracts, Workshop Work Scheduling, Project Management, Planning Experiments, Printed Circuit Board Production.
Intelligent Interfaces:
Hardware (fiscal) Instrumentation, Computer programs, Multiple Databases, Control Panels.
Natural Language Systems:
Interfaces with natural language databases, Tax Management (Accounting Aids), Legal Consulting, Farm Planning, Banking Systems Survey.
Design Systems:
Very high-scale microcircuit integration, Synthesis of electronic circuits, Chemical Plants, Buildings, Bridges and dams, Conveyor systems.
Computer Vision Systems:
Software Development:
Automatic programming.
Voice recognition programs to book airline tickets for a flight.
Expert systems that control the proper functioning of a space shuttle.
Expert Disease Diagnostic Systems.
Credit card and account fraud protection through neural network systems expert systems.
Detection of small anomalies invisible to the human eye on X-rays.
Voice Messaging Systems.
In the world of video games.
Rivals with logical behavior.
Automatic Translation of Documents.
Systems That Think Like Humans:
These systems try to emulate human thought.; for example, artificial neural networks The automation of activities that we link to human thought processes, activities such as Decision Making , Troubleshooting, learning
Systems That Act Like Humans:
These systems try to act like humans.; I mean, mimic human behavior; e.g. robotics The study of how to get computers to perform tasks that, for the time being, Humans do better.
Systems That Think Rationally:
That is to say, with logic (ideally), They try to imitate, emulate, the rational logical thinking of human beings; for example, expert systems The study of the calculations that make it possible to perceive , Reason and act.
Systems that act rationally (ideally):
The first period of Artificial Intelligence, Sub-symbolic call, dates from approximately 1950 to 1965. This period used numerical representations ( sub-symbolic) of knowledge. Although most of the books on Artificial Intelligence emphasize the work done by Rosenblatt and Widrow with neural networks during this period., The reality is that another important sub-symbolic school Knowledge also from the same era and these are evolutionary algorithms..
The classical school within Artificial Intelligence, uses symbolic representations based on a finite number of primitives and rules for symbol manipulation. The symbolic period is considered roughly between 1962 and 1975, followed by a period dominated by knowledge-based systems from 1976 to 1988. However, In this second period the symbolic representations (for example, Semantic networks, predicate logic, etc.) remained a central part of those systems..
Logic Programming has its closest origins in the works of J. To. Robinson, who proposed in 1965 a rule of inference which he called, by which the proof of a theorem can be carried out automatically.
Resolution is a rule that applies to certain types of formulas in the First Order Predicate Calculus., The so-called clauses and the proof of theorems under this rule of inference is carried out by reductio ad absurdum..
Other Important Works of That Era That Influenced Logic Programming, were Loveland's, Kowalski & Inexperienced, that designs a theorem tester that extracts from the proof the value of the variables for which the theorem is valid.
These testing mechanisms were worked on with great enthusiasm for a time, but, because of its inefficiency, were relegated until the birth of Prolog, which emerged in 1971 at the University of Marseille, France.
It is also known as symbolic-deductive AI. It is based on the formal and statistical analysis of human behavior in the face of different problems:
That they have autonomy and can self-regulate and control themselves to improve.
Computational intelligence (also known as sub-symbolic-inductive AI and strong AI) involves iterative learning development (. Iterative Modifications of Parameters in Connectionist Systems). Learning is based on empirical data. Some methods in this branch include:
Vector Machine Stand:
Systems that enable high-power generic pattern recognition.
Neural Networks:
Hidden Markov Models:
Fuzzy systems:
Techniques for Achieving Reasoning Under Uncertainty. It has been widely used in modern industry and consumer products, Like washing machines.
Evolutionary Computation:
It is remarkable how technology today has developed to points perhaps unimaginable a few decades ago... Just Years Ago. The variety and speed of a PC's functions lead us to think... our brains will be inferior to machines...?
I think if someone is asked this question and they should respond in an impulsive and quick manner, It could go so far as to say that machines are smarter.". That would not be a totally wrong answer, Nowadays the machines perform, for example, Very complicated mathematical calculations in seconds, They search for information in seconds too. This could cause people to thoughtlessly reply that machines are the smartest.
Personally, I dare to criticize this answer. The rationale is simple, We know that human beings are not perfect, There won't be a single time when we don't make the slightest mistake; that's why something imperfect can't make something perfect.? Simplified. Isn't Microsoft flawed ? This was corroborated by Paul in the previous submission, And I'm guessing the other operating systems are also made up of glitches, Although they may be small, they are not discovered.
Another of my arguments is the variety of what we call intelligence. It's not just everything that has to do with science of some kind. There is also what is called emotional intelligence, that is, that type of intelligence that encompasses the ability to recognize one's own emotions and those of others. I guess a machine can't determine a person's mood.
Truly, Artificial intelligence consists of the assimilation of the inductive and deductive processes of the human brain. This Attempt at Imitation Faces Harsh Hardware Restrictions. A computer is not a brain; Its electronic complexity is at an abysmal distance from the superior neurological complexity of the brain. Artificial intelligence accepts the challenge of mimicking the processes of the brain by applying a lot of ingenuity to take advantage of the means available and that are elaborated.
Whatever the application, the LA is based on the following two elements:
Smart Behavior Strategies.
These elements form a coherent construction: they are form and content, Structure and Matter. The first element is that of intelligent behavior strategies; It is combined in the arrangement of rules for formulating good inferences, conjectures, and, also, in its usefulness in the search for a solution to the question posed. In this way,, Strategies are the formal structural part.
By Opposition, The second element signifies the material, the content, and, therefore, varies in each case in a more profound way; It's all about knowledge. In fact, You can't pretend to gather knowledge, but knowledge. For example, Each expert system possesses in memory all the distinctive knowledge that a specialist in the field would have, Be a Doctor, A Lawyer A Chemist. The knowledge that is collected has a specialized character and reaches a considerable conceptual volume.
In principle, the work will be done from a philosophical approach, as we focus on knowledge and overcoming human limits, artistic, since, A reading of cybernetic art can also be made through complexity theory and cognition technologies, But it will also have a biological aspect because the cognitive sciences are highly interdisciplinary and encompass fields such as ; Cognitive psychology, Neurolinguistics, neurophysiology.
Systems that act like humans (Your Ring Test Approach)
Critics often underline the fact that we should characterize what it is to act as human. To do this, Of course, The system must have a knowledge base (symbolic) and a process that must use pure language, Something it still doesn't do. Another group of criticisms against this approach is given by the fact that it forgets aspects as essential to human action as emotions, Feelings, Morality, etc.
Systems That Think Like Humans (Cognitive Approach)
To be able to build this kind of systems, It would be necessary to start from a certain definition of thinking. The main task, for this approach, would be to formalize a model of thought.
Systems that think rationally (Logical Approach)
The ancestors of this approach are Aristotle and Classical Logic. According to this paradigm, The rational thing to do is to reason logically.
Systems that act rationally (Rational Agent Approach)
This is an integrative approach to learning and reasoning.
The concept of AI is still too vague. Contextualizing, and taking into account a scientific point of view, We could encompass this science as the one in charge of imitating a person, And not your body, but imitate the brain, in all its functions, invented in the human being invented on the development of an intelligent machine.
Sometimes, applying the definition of Artificial Intelligence, Thinking of intelligent machines without feelings, that "hinder" finding the best solution to a given problem.
Many of us think of artificial devices capable of concluding thousands of premises from other given premises, without any kind of emotion having the option to hinder this work.
Along these lines, You have to know that intelligent systems already exist. Able to make "right" decisions.
Although, for the time being, most researchers in the field of Artificial Intelligence focus only on the rational aspect, Many of them are seriously considering the possibility of incorporating "emotive" components as indicators of status, to increase the efficiency of intelligent systems.
Particularly for mobile robots, It is necessary for them to have something related to emotions in order to know – at all times and at least- What to do next.
By having "feelings" and, at least potentially, "Motivations", they will be able to act in accordance with their "intentions".
Like this, A robot could be equipped with devices that control its internal environment; for example, who "feel hungry" when they sense that their energy level is dropping, who "feel afraid".
Here is a list of some of the many that exist within the study of Artificial Intelligence and even many of these are considered topical concepts by many.
Artificial Intelligence Logistics
Programming systems that have a database with common knowledge about the world around them and within these have information on how to react to specific situations. The purpose of these systems is to represent solutions to problems in sentences using a mathematical language such as an algorithm. The emphasis is made through the analysis of information and the reaction of the information according to its data source.
Artificial Intelligence systems, many of them, are based on examining large numbers of possibilities within the search for a solution, movement by the system. An example of these is the ability to analyze a move of pieces in a game of chess, where he evaluates millions of possibilities in a second and according to the reasoning of this he makes his decision.
The systems will illustrate in their tasks facts of the world around them and those that they have enough knowledge to be able to represent the information in a mathematical language.
The systems sometimes obtain data that is feasible but sometimes it does not exist in order to understand the decision process. This being the case, the system, based on past actions, can deduce certain tasks, solutions, according to mathematical calculations made by the system. To achieve these you have to have been in similar situations otherwise you will not react to the situation. This is what is known as Monotony Inference, where a conclusion is reached by swaying the alternatives and according to the situation it can be changed.
Knowledge, Common Sense and Reasoning
Although they are really far from the human being in terms of these capacities, the end of all Artificial Indiligence begins and ends here. He mentions this because getting a computer to analyze and react to different situations, this is the common goal of this whole field.
Experiential learning
Systems will learn to react and act according to previous situations, In other words, the system will take into account past decisions to react to current situations. As he gains experience in similar situations, he files them in his database as memory.
The systems in this field contain data that contains a number of levels and it is according to the information at these levels that the system reacts to the situation. The system reacts to the situation by means of the level of the specific situation and searches its database for alternatives for this situation.
It is the study of the different knowledge that we have to solve problems in our environment.
Study of the things that exist in the world, where the different kinds of objects and their relationship with the environment around them are studied.
Genetic Programs
They are a system that has a technical programming that solves tasks according to the alternatives previously used in other problem tasks.
Artificial Intelligence (AI) It is as old as computer science and has generated ideas, Techniques and applications that have made it possible to solve difficult problems.
Far from staying there, The future of this technology involves new advances such as the development of software that makes our lives easier, helping us make decisions in complex environments by allowing us to solve difficult problems.
In this context, Researchers are increasingly emphasizing the creation of systems capable of learning and displaying intelligent behaviors without the corset of trying to replicate a human model.. This is at least one of the main conclusions of the Fourth International Seminar on New Topics in Artificial Intelligence, recently organized by the SCALAB group of the Department of Computer Science of the Carlos III University of Madrid (UC3M).
In this context, five leading scientists presented their latest advances in their research work on different aspects of AI. The speakers ranged from the most theoretical questions, as algorithms capable of solving combinatorial problems, to robots that reason about emotions, Systems that use vision to track activities Automatic players learning how to win in a given situation.
The different contributions in this seminar made it clear that this technological field is very active and provides solutions to very different sectors. In addition, New lines of research are constantly opening up and there is still a lot of room for improvement in the transfer of knowledge between researchers and industry.
In the same way, the meeting brought out the promising future of AI, which, in the opinion of the researchers of the SCALAB group, contemplates an explosion in the number of devices capable of capturing and processing information, which, Along with the growth of computing power, advances in algorithms, Skyrockets the possibilities of practical application.
Among other things, AI will enable advances in the development of systems capable of automatically understanding the situation and context from data from sensors and information systems and establishing action plans, in Decision Support Applications in Dynamic Conditions. This is because, According to the researchers, to the rapid advancements and availability of sensor technologies that provide a continuous flow of data about the environment, Information that must be treated appropriately in a data and information fusion node. And also to the development of sophisticated task planning techniques that allow action plans to be composed, Execute these plans, check its correct execution, rectify plans in case of failures and learn from mistakes made.
These technologies have enabled the approach of a wide range of applications such as integrated surveillance systems, Monitoring and Anomaly Detection, Recognition of activities, Tele-care systems, Transport Logistics Planning, and so forth. According to Antonio Chella, Professor at the University of Palermo and expert in Artificial Consciousness, the future of AI will involve discovering a new meaning of the word intelligence.". Until now, It has been equated with automatic reasoning in software systems, but in the future, AI will encompass more daring concepts such as the embodiment of intelligence in robots, emotions and above all consciousness.
Take a look at de Tú ring ( Test Your Ring) is a test proposed by Alan Tu ring to prove the existence of intelligence in a machine. It was exposed in 1950 in an article (Computing equipment and intelligence) for Mind magazine, and remains one of the best methods for AI advocates.
It is based on the positivist hypothesis that, if a machine behaves in all respects as intelligent, then you must be smart.
The test is a challenge. A judge is supposed to be in a room, a machine and a human being in others. El juez debe descubrir cuál es el ser humano y cuál es la máquina, estándoles a los dos permitido mentir al contestar por escrito las preguntas que el juez les hiciera. La tesis de Tú ring es que si ambos jugadores eran suficientemente hábiles, el juez no podría distinguir quién era el ser humano y quién la máquina. Todavía ninguna máquina puede pasar este examen en una experiencia con método científico.
En 1990 se inició un concurso, el Premio Loebner, una competición de carácter anual entre programas de ordenador que sigue el estándar establecido en la prueba de Tú ring. Un juez humano se enfrenta a dos pantallas de ordenador, una de ellas que se encuentra bajo el management de un ordenador, y la otra bajo el control artificial intelligence blog de un humano. El juez plantea preguntas a las dos pantallas y recibe respuestas. El premio está dotado con 100.000 dólares estadounidenses para el programa que pase el take a look at, y un premio de consolación para el mejor programa anual.
La primera y única vez que un juez confundió a una máquina con un humano fue en el año 2010, cuando el robot Suzette, de Bruce Wilcox, superó la prueba.
Existe otra prueba parecida, propuesta por John Searle y popularizada por Roger Pen rose: the “sala china”, para argumentar que la máquina no ha superado la Prueba de Turing.2 En esencia, es igual en la forma, pero se realiza con personas encerradas en una habitación y se requiere que estas no conozcan el idioma en que se realiza la conversación. Para ello se usa un diccionario que permite confeccionar una respuesta a una pregunta dada, sin entender los símbolos.
Como consecuencia, se argumenta que por mucho que una persona sea capaz de enviar una cadena de símbolos en chino relacionada con otra cadena recibida, no quiere decir que sepa chino, sino que sabe aplicar un conjunto de reglas que le indican lo que ha de enviar. Falta la semántica en el proceso y por eso es muy cuestionada como inteligencia artificial, puesto que equipara una máquina pensante con una que parece que piensa. Ray Kurzweil predice que el ordenador pasará la prueba de Tú ring hacia el 2029, basado en el concepto de singularidad tecnológica.
Artificial life is the study of life and artificial systems that exhibit properties similar to living things., through simulation models. Scientist Christopher Langton was the first to use the term in the late 1980s when the “First International Conference on the Synthesis and Simulation of Living Systems” (also known as Artificial Life I) at Los Alamos National Laboratory in 1987.
The artificial living area is a meeting point for people from other more traditional areas such as linguistics, physics, mathematics, philosophy, psychology, Computer Science, biology, anthropology and sociology in which it would be unusual for theoretical and computational approaches to be discussed.
As an area, has a controversial history; John Maynard Smith criticized certain artificial life works in 1995 as “Science without facts”, and generally hasn't received much attention from biologists..
However, the recent publication of articles on artificial life in widely circulated journals,1 como Science y Nature son evidencia de que las técnicas de vida artificial son cada vez más aceptadas por los científicos, at least as a method of studying evolution.
Estudio de sistemas artificiales que muestran comportamientos característicos de los sistemas vivos reales. Término acuñado a finales de los 80s por Christopher Langton al realizar la primera conferencia sobre el tema en Los Alamos Nationwide Laboratory in 1987, bajo el nombre deInternational Conference on the Synthesis and Simulation of Dwelling Programs”.
Los investigadores en vida artificial a menudo son divididos en 2 grandes grupos:
La posiciónfuertedefiende que la vida es un proceso que puede ser abstraído de cualquier medio concreto.
La posiciónsuaveniega la posibilidad de que pueda existir un proceso vivo fuera de la química del carbono. Los investigadores que trabajan en esta línea intentan emular procesos relacionados con la vida para conseguir entender fenómenos simples.
El objetivo del estudio de la vida artificial no es solamente crear modelos biológicos de seres vivos, sino investigar los principios fundamentales de la vida en sí misma. Estos pueden ser estudiados incluso a través de modelos de los que no exista un equivalente físico directo.
Sistemas inteligentes
Es un programa de computación que reúne características y comportamientos asimilables al de la inteligencia humana animal.
The expression “Intelligent system” sometimes used for incomplete intelligent systems, For example for a smart home an expert system.
A complete intelligent system includes “senses” that allow you to receive information from your environment. Can act, and has a memory to archive the result of its actions. It has an objective and, Inspecting Your Memory, You can learn from your experience. Learn how to improve your performance and efficiency.
Para que un sistema inteligente pueda ser considerado completo, debe incluir diversas funcionalidades que incluyan:
There are many definitions of “intelligence”. For practical uses we use this: Intelligence is the level of the system in achieving its objectives.
A system is part of the universe, with a limited extension in space and time. Parts of the system have more, stronger, Correlations with other parts of the same system; than with parts outside the system.
A goal is a certain situation that the intelligent system wants to achieve.. There are usually many levels of goals, There may be one main objective and many sub-objectives.
Sensory capacity:
A sense is the part of the system that can receive communications from the environment. The senses are needed so that the intelligent system can know its surroundings and act interactively..
A concept is the basic element of thought. It's physical storage, materials de información (in electron neurons). Todos los conceptos de la memoria están interrelacionados en purple. The ability to conceptualize involves the development of levels of abstraction.
Rules of action:
A rule of action is the result of an experience the result of interpreting one's own memory. Relates situation and consequences of action.
Memory is a physical storage of concepts and rules of action. This includes system experience.
Learning is probably the most important capability of an intelligent system. The system learns concepts from information received from the senses. Aprende reglas de actuación a base de su experiencia. The performance, sometimes made randomly, is stored with its value. An action rule increases in value if it allowed the achievement of an objective. Learning includes fixing abstract concepts, based on concrete examples and the creation of composite concepts that contain the concepts of parts of an object. Learning is also the ability to detect relationships (Patterns) between the “situation” and the part “Future situation” of an action rule.
Una purple neuronal artificial (ANN) es un esquema de computación distribuida inspirada en la estructura del sistema nervioso de los seres humanos. La arquitectura de una red neuronal es formada conectando múltiples procesadores elementales, siendo éste un sistema adaptivo que posee un algoritmo para ajustar sus pesos (parámetros libres) para alcanzar los requerimientos de desempeño del problema basado en muestras representativas.
Por lo tanto podemos señalar que una ANN es un sistema de computación distribuida caracterizada por:
Un conjunto de unidades elementales, cada una de las cuales posee bajas capacidades de procesamiento.
Una densa estructura interconectada usando enlaces ponderados.
Parámetros libres que deben ser ajustados para satisfacer los requerimientos de desempeño.
Un alto grado de paralelismo.
Es importante señalar que la propiedad más importantes de las redes neuronales artificiales es su capacidad de aprender a partir de un conjunto de patrones de entrenamientos, I mean, es capaz de encontrar un modelo que ajuste los datos. El proceso de aprendizaje también conocido como entrenamiento de la purple puede ser supervisado no supervisado.
El aprendizaje supervisado consiste en entrenar la red a partir de un conjunto de datos patrones de entrenamiento compuesto por patrones de entrada y salida. El objetivo del algoritmo de aprendizaje es ajustar los pesos de la crimson w de manera tal que la salida generada por la ANN sea lo más cercanamente posible a la verdadera salida dada una cierta entrada. That is to say, la purple neuronal trata de encontrar un modelo al procesos desconocido que generó la salida y. Este aprendizaje se llama supervisado pues se conoce el patrón de salida el cual hace el papel de supervisor de la pink.
En cambio en el aprendizaje no supervisado se presenta sólo un conjunto de patrones a la ANN, y el objetivo del algoritmo de aprendizaje es ajustar los pesos de la pink de manera tal que la crimson encuentre alguna estructura configuración presente en los datos.
La realidad digital se refiere a las simulaciones en un ordenador del mundo real por medio de imágenes tridimensionales y componentes externos como un casco para permitir que los usuarios interactúen con la simulación. Los usuarios se mueven por una realidad virtual como si estuviesen en un mundo real.
El auge de la realidad digital ha estado precedido de un largo tiempo de intensa investigación. Today, la realidad virtual se plasma en una multiplicidad de sistemas que permiten que el usuario experimente “artificially”, sin embargo ha tenido diversos aportes entre los que destacan:
En 1958 la Philco Corporation desarrolla un sistema basado en un dispositivo visible de casco controlado por los movimientos de la cabeza del usuario.
En el inicio de los 60, Ivan Sutherland y otros crean el casco visor HMD mediante el cual un usuario podía examinar, moviendo la cabeza, un ambiente gráfico. Simultáneamente Morton Heilig inventa y opera el Sensorama.
Para 1969, Myron Krueger creó ambientes interactivos que permitían la participación del cuerpo completo, en eventos apoyados por computadoras.
En 1969 la NASA puso en marcha un programa de investigación con el fin de desarrollar herramientas adecuadas para la formación, con el máximo realismo posible, de posteriores tripulaciones espaciales.
En el inicio de los 70, Frederick Brooks logra que los usuarios muevan objetos gráficos mediante un manipulador mecánico.
A fines de los 70, en el Media Lab. del instituto tecnológico de Massachusetts MIT, se obtiene el mapa filmado de Aspen, una simulación de vídeo de un paseo a través de la ciudad de Aspen, Colorado. Un participante puede manejar por una calle, bajarse y hasta explorar edificios.
También en los 70, Marvin Minsky acuña el términoTELEPRESENCIA”, para definir la participación física del usuario a distancia.
William Gibson, al inicio de los eighty, publica la novelaNeuromancerdonde la trama se desarrolla en base a aventuras en un mundo generado por computadora al que denomina CIBERESPACIO.
Las empresas Disney producen la películaTRON”.
Tom Zimmerman inventa el Dataglove.
Jaron Lanier acuña el término de Realidad Digital, concretando la variedad de conceptos que se manejaban en esa época.
En 1984, Michael McGreevy y sus colegas de la NASA desarrollan lentes de datos con los que el usuario puede ahora mirar el inside de un mundo gráfico mostrado en computadora.
Después de 1980 aparece el HOLODECK en la serie de TELEVISION Begin Trek; este es un ambiente generado por computadora, con figuras holográficas para entretenimiento de la tripulación.
Para el inicio de los ninety los sistemas de realidad digital emergen de los ambientes de laboratorio en búsqueda de aplicaciones comerciales.
Para el año 1995 los simuladores de vuelo, desde los más perfectos, como los que utilizaban Thomson-Militaire Dassault, hasta los videojuegos para microordenadores son en sí aplicaciones de la realidad virtual, cuyo fin es situar a la persona en situaciones comparables a la experiencia real.
Un grupo de investigadores de IBM desarrolla un prototipo informático para la creación de realidad virtual. Este sistema generaba modelos del mundo real basados en representaciones tridimensionales y estereoscópicas de objetos físicos con los que pueden interactuar varias personas simultáneamente.
Today, se plasma en una multiplicidad de sistemas, el más conocido es la empresa norteamericana VPL Analysis, junto con la que la NASA que trabaja en el desarrollo de sus propias aplicaciones.
Se desarrolló una arquitectura básica para el desarrollo de una variedad casi ilimitada de laboratorios virtuales. Así también, en otros campos, como la medicina, economía y exploración espacial, utilizan los laboratorios virtuales para una gran variedad de funciones. Ejemplo, los cirujanos pueden realizar operaciones simuladas para ensayar las técnicas más complicadas. Los arquitectos pueden hacer que sus clientes, dándoles la oportunidad de que abran las puertas las ventanas y enciendan apaguen las luces de la obra a realizar.
En ingeniería se desarrollan aplicaciones para aéreo-industria, industria automovilística (en modelos electrónicos de vehículos para probar confort, opciones, etc.).
Today, la realidad digital se plasma en una multiplicidad de sistemas, el más conocido de los cuales es el que ha desarrollado la empresa norteamericana VPL Analysis (Visual Programming Language), con la que la NASA trabaja en estrecha colaboración en el desarrollo de sus propias aplicaciones.
Se desarrolló una arquitectura básica para el desarrollo de una variedad casi ilimitada de laboratorios virtuales. En ellos, los científicos de disciplinas muy diversas son capaces de penetrar en horizontes antes inalcanzables gracias a la posibilidad de estar ahí: dentro de una molécula, en medio de una violenta tormenta en una galaxia distante.
Profesionales de otros campos, como la medicina, economía y exploración espacial, utilizan los laboratorios virtuales para una gran variedad de funciones. Los cirujanos pueden realizar operaciones simuladas para ensayar las técnicas más complicadas, antes de una operación real. Los economistas exploran un modelo de acción de un sistema económico para poder entender mejor las complejas relaciones existentes entre sus distintos componentes.
Los astronautas tienen la posibilidad de volar sobre la superficie simulada de un planeta desconocido y experimentar la sensación que tendrían si estuvieran allí.
Los arquitectos pueden hacer que sus clientes, enfundados en cascos y guantes, visiten los pisos-piloto en un mundo de Realidad Virtual, dándoles la oportunidad de que abran las puertas las ventanas y enciendan apaguen las luces del apartamento. On the other hand, permite la anticipación de errores de diseño y experiencias físicas con ambientes no construidos.
Con el fin de simplificar las comunicaciones con los inversores de otros países, se ha modelizado por completo en sistema VPL, el proyecto de acondicionamiento del puerto de Seattle. Ambas partes juegan así sus cartas virtuales en el proyecto, sobrevolando los canales y obras portuarias y acercándose a ellas para apreciar los detalles con sólo flexionar los dedos.
El ámbito científico no se queda al margen, investigadores de la Universidad de Carolina del Sur estudian moléculas complejas, desplazando grupos de átomos mediante un instrumento, una simbiosis entre los punteros (del tipo del ratón) y el Dataglove.
En el área de defensa y de la investigación espacial nuclear, donde se han producido los avances más espectaculares. Thomson-Militaire dispone de un sistema utilizado para simulaciones calificadas de alto secreto. El CNRS y la Comexe poseen, asimismo equipos que les permiten realizar simulaciones en medios hostiles: reparaciones en el interior de un reactor nuclear, for example, la NASA realiza prácticas de montaje de satélites a distancia utilizando técnicas de Realidad Digital.
En Francia Videosystem utiliza el sistema Jaron Lanier para aplicaciones de apoyo a largometraje en cuanto a las cámaras, vestuario de actores, escenarios y otros.
La empresa británica W-Industries dispone de un sistema propio de realidad digital, bautizado con el nombre de Virtuality, el cual es utilizado para videojuegos, en el área de defensa y medicina, así como en la Arquitectura y diseño utilizando una versión para UNIX del software CAD.
En educación y adiestramiento se da la exploración de lugares y cosas inaccesibles por otros medios. Creación de lugares y cosas con diferentes cualidades respecto a los que existen en el mundo real. Interacción con otras personas, ubicadas en áreas remotas, de intereses afines. Colaboración en la realización de proyectos con estudiantes alrededor del mundo.
En ingeniería se desarrollan aplicaciones para aereo-industria, industria automovilística (en modelos electrónicos de vehículos para probar confort, opciones, and so on.).
Responde a la metáfora de mundo” que contiene objetos” y opera en base a reglas de juego que varían en flexibilidad dependiendo de su compromiso con la Inteligencia Artificial.
Se expresa en lenguaje gráfico tridimensional.
Abre las alternativas donde el único límite es la imaginación del hombre.
Hoy en día existen muchas aplicaciones de entornos de realidad virtual con éxito en muchos de los casos. En estos entornos el individuo solo debe preocuparse por actuar, ya que el espacio que antes se debía imaginar, es facilitado por medios tecnológicos.
Nevertheless, muchos expertos coinciden en señalar que es posible que dentro de algunos años, pueda llegarse a lograr este objetivo, y que la realidad virtual se convierta en una materia cotidiana, gracias a la evolución del mercado orientado al desarrollo de equipamiento acorde y asequible.
SISTEMAS VENTANAS (Window on World Techniques):
Se han definido como sistemas de Realidad Digital sin Inmersión.
Algunos sistemas utilizan un monitor convencional para mostrar el mundo digital. Estos sistemas son conocidos como WOW (Window on a World) y también como Realidad Digital de escritorio.
Estos sistemas tratan de hacer que la imagen que aparece en la pantalla luzca real y que los objetos, en ella representada actúen con realismo.
Este enfoque se basa en la filmación, mediante cámaras de vídeo, de una más personas y la incorporación de dichas imágenes a la pantalla del computador, donde podrán interactuaren tiempo realcon otros usuarios con imágenes gráficas generadas por el computador.
In this way,, las acciones que el usuario realiza en el exterior de la pantalla (ejercicios, bailes, and so on.) se reproducen en la pantalla del computador permitiéndole desde fuera interactuar con lo de dentro. El usuario puede, a través de este enfoque, simular su participación en aventuras, deportes y otras formas de interacción física.
Otra interesante posibilidad del mapeo mediante vídeo consiste en el encuentro interactivo de dos más usuarios a distancia, pudiendo estar separados por centenares de kilómetros.
Este tipo de sistemas puede ser considerado como una forma specific de sistema inmersivo.
Los más perfeccionados sistemas de Realidad Virtual permiten que el usuario pueda sentirse sumergido” en el inside del mundo digital.
El fenómeno de inmersión puede experimentarse mediante 4 modalidades diferentes, dependiendo de la estrategia adoptada para generar esta ilusión. Ellas son:
to) El operador aislado
b) La cabina private
d) La caverna cueva (cave)
Estos sistemas inmersivos se encuentran generalmente equipados con un casco-visor HMD. Este dispositivo está dotado de un casco máscara que contiene recursos visuales, en forma de dos pantallas miniaturas coordinadas para producir visión estereoscópica y recursos acústicos de efectos tridimensionales.
Una variante de este enfoque lo constituye el hecho de que no exista casco como tal, sino un visor incorporado en una armadura que libera al usuario del casco, suministrándole una barra (como la de los periscopios submarinos) que permite subir, bajar controlar la orientación de la imagen obtenida mediante el visor.
Otra forma interesante de sistemas inmersivos se basa en el uso de múltiples pantallas de proyección de gran tamaño dispuestas ortogonalmente entre sí para crear un ambiente tridimensional caverna (cave) en la cual se ubica a un grupo de usuarios. De estos usuarios, hay uno que asume la tarea de navegación, mientras los demás pueden dedicarse a visualizar los ambientes de Realidad Digital dinamizados en tiempo real.
Esta tecnología vincula sensores remotos en el mundo real con los sentidos de un operador humano. Los sensores utilizados pueden hallarse instalados en un robot en los extremos de herramientas tipo Waldo. De esta forma el usuario puede operar el equipo como si fuera parte de él.
Esta tecnología posee un futuro extremadamente prometedor. La NASA se propone utilizarla como recurso para la exploración planetaria a distancia.
La tele presencia contempla, obligatoriamente, un grado de inmersión que involucra el uso de control remoto, pero tiene características propias lo suficientemente discernibles como para asignarle una clasificación specific.
Al fusionar los sistemas de tele presencia y realidad digital obtenemos los denominados sistemas de Realidad Mixta. Aquí las entradas generadas por el computador se mezclan con entradas de telepresencia y/ la visión de los usuarios del mundo real.
Este tipo de sistema se orienta a la estrategia de realzar las percepciones del operador usuario con respecto al mundo real. Para lograr esto utiliza un tipo esencial de HMD de visión transparente (see trouhg), que se apoya en el uso de una caminadora que es una pantalla especial, la cual es transparente a la luz que ingresa proveniente del mundo actual, pero que a la vez refleja la luz apuntada a ella mediante los dispositivos ópticos ubicados en el interior del HMD.
En este sentido se percibe un prometedor mercado para los sistemas de Realidad Mixta en industrias y fábricas donde el trabajador debe llevar a cabo operaciones complejas de construcción mantenimiento de equipos e instrumentos.
Este sistema combina un monitor de despliegue estereoscópico utilizando lentes LCD con obturador acoplados a un rastreador de cabeza mecánico. El sistema resultante es superior a la easy combinación del sistema estéreo WOW debido a los efectos de movimientos introducidos por el rastreador.
Este sistema combina estímulos visuales, auditivos, táctiles, de movimientos, con aplicaciones de I.A y percepción que hace que el mundo virtual casi sea actual Ej.: los nuevos sistemas de entrenamiento del ejército norteamericano.
Desde hace un tiempo el concepto marketiniano de Reputación On-line, está muy presente como un elemento clave en la estrategia de comunicación. Hay un cierto miedo, a que la reputación caiga velozmente debido a la potencia de difusión de un canal como internet.
Se supone que es sencillo para alguien opinar en foros, criticar acertadamente desprestigiar por sistema una empresa, una marca una persona. Existe la sensación de que las marcas están todavía más expuestas en el terreno digital. En mi opinión, el rumor, la crítica, el bulo existía antes de que tuviéramos acceso a las medios modernos con los que hoy nos comunicamos.
Internet lleva ya los suficientes años con nosotros para haber pasado por diferentes etapas. En todos estos años, hemos ido aprendiendo a sacar partido de los recursos que nos ofrece. Hemos hecho búsquedas de todo tipo para resolver las dudas que nos asaltaban (gracias a Google por existir). Compramos cualquier artículo en cualquier lugar del mundo, incluso regateamos (Ebay).
Buscamos trabajo lo contratamos (portales de empleo como Infojobs). Planificamos nuestros viajes mirando siempre que referencias y recomendaciones nos da la red. Entregamos momentos, fotos, vídeos, opiniones, and so on. Una cantidad de información, impensable hace poco tiempo.
Ahora compartimos con el resto de la purple quienes somos, que hacemos, que nos gusta, con quien nos gusta estar… Y esto supone un cambio de enfoque notable.
La separación entre nuestra actividad digital y la actual, antes estaba mucho más marcada. Me atrevería a decir que actualmente, esa línea es difusa.
Y es que hoy en día nos encontramos en una fase más adulta. En la que nos presentamos en web, como somos realmente, olvidando la época de usar nombres inventados y personalidades dudosamente creíbles.
Actualmente buscamos la autenticidad, a la persona las personas que hay detrás de lo digital, y una consecuencia positiva es que somos más tolerantes con la no perfección de lo humano. Entendemos y comprendemos los posibles errores y aceptamos mejor las disculpas. La empatía gana en importancia.
Therefore, vemos que existe una fusión de los dos mundos anteriormente separados. Lo físico y lo digital están unidos. Este hecho, influye en la comunicación de las organizaciones de cualquier tamaño, que no pueden permitirse dar un mensaje equivocado de quienes son. La sociedad demanda transparencia, cercanía, diálogo y las entidades que no sepan entenderlo, estarán alejándose de su público objetivo.
Trabajar en una comunicación coherente, para que seamos reconocibles, fiables y respetables no es una opción, el que no lo haga toma el riesgo de quedarse solo, y estamos en un mundo, sin ningún género de duda, cada día más social.
8. Sistemas inmersos
Para poder hablar de sistemas inmersos debemos hablar un poco de cómo se entiende el concepto de un sistema inmerso, podemos decir del mismo que es un sistema basado en un microprocesador cuyos componentes físicas e informáticas (hardware y software) están desarrollados, diseñados y optimizados para poder resolver un problema de manera más eficiente tratando de reducir costos y mejorando el rendimiento del proceso.
También podemos citar de los mismos que su funcionamiento es similar a los de una pequeña computadora donde para poder resolver fines más concretos se reduce la velocidad de respuesta ajustándolos a resolver los problemas concretos que son necesarios para poder resolver de manera más eficiente una actividad.
Los sistemas inmersos tienen gran cantidad de aplicaciones, que van desde controles industriales fabricación de equipos médicos, de telecomunicación que necesitan unos sistemas mas eficientes para poder resolver problemas más específicos, podemos citar por ejemplo la maximización de un receptor de señales de audio para poder recibir señales prefijadas de mayor calidad y brindar mejor servicio a sus usuarios.
Lo importante de los sistemas inmersos es la capacidad de mejorar el rendimiento de un equipo crear otro con fines específicos para mejorar el rendimiento del mismo, el conjunto de nuevos componentes que se logra insertar dentro de un sistema lo convierte en un nuevo sistema inmerso.
Nosotros podemos darnos cuenta que hablar de sistemas inmerso es hablar de innovación, development, mejora, investigación y pruebas, como estudiantes de ingeniería nosotros tener que conseguir la habilidad de construir, desarrollar y supervisar el funcionamiento y sobre todo creación de un sistema inmerso, al asegurarnos que podemos construir uno podemos estar satisfechos con la calidad de profesionales que llegamos a hacer.
Podemos brindar con la creación de sistemas inmerso lo que se quiere una mejora continua en las especificaciones (tipo de proceso) en la calidad y que se encuentre avalado por un costo que lo mantenga competitivo.
Lo que generalmente caracteriza a un sistema inmerso es el ingenio del que lo construye, ya que se deben hacer modificaciones adaptaciones que no se encuentran estipuladas, uno debe inventarse pero esto solo se logra mediante investigación de lo que queremos mejorar, ya que solo lo podemos mejorar si lo conocemos a la perfección tratando de romper sus barreras de aplicación mediante la adaptación del mismo.
inmersiones simples,
inmersiones continuadas
Inmersiones simples:
Son aquellas que dejan pasar 12 horas, entre inmersión e inmersión.
Inmersiones continuadas:
El tiempo de espera entre inmersión e inmersión es de menos de 10 minutos.
Para las tablas de compresión este tipo cuenta como simple, tomando la máxima profundidad alcanzada en cualquiera de las inmersiones, y sumando los tiempos de las inmersiones.
Inmersiones sucesivas repetitivas:
Son aquellas que han pasado más de 10 minutos pero menos de 12 horas entre inmersión e inmersión realizadaTiempo de inmersión y velocidad de ascenso
El tiempo se calcula desde que se inicia el descenso hasta el momento en el que volvemos a estar en la superficie.
La realidad digital puede ser de dos tipos:
La Realidad Virtual Inmersiva:
con frecuencia estan ligados a un ambiente tridimensional creado por computadoras, el cual se manipula a través de cascos, guantes u otros dispositivos que capturan la posición y rotación de diferentes partes del cuerpo humano.
La Realidad Virtual no inmersiva:
La realidad virtual no inmersiva utiliza medios como el que actualmente se ofrece Web en el cual se puede interactuar en tiempo actual con diferentes personas en espacios y ambientes que en realidad no existen sin la necesidad de dispositivos adicionales a la computadora. ofrece un nuevo mundo a través de una ventana de escritorio. Este enfoque no inmersivo tiene varias ventajas sobre el enfoque inmersivo como: bajo costo y fácil y rápida aceptación de los usurarios. Los dispositivos inmersivos son de alto costo y generalmente el usurario prefiere manipular el ambiente digital por medio de dispositivos familiares como son el teclado y el ratón que por medio de cascos pesados guantes.
En un principio la realidad digital fue usada en su mayoría para aplicaciones militares incluso de entretenimiento, However, en los últimos años se han diversificado las áreas en que se utiliza. En las secciones anteriores, se mencionó los diferentes tipos de realidad digital y sus áreas de ingerencia, aquí se explora más a fondo los distintos proyectos que existen relacionadas con esta tecnología. Se describirán proyectos de distintos tipos: visualización -una de las facetas más fascinantes de la realidad virtual-, manipulación de robots, medicina, among others.
Realidad virtual en la IngenieríaDentro de las áreas de ingeniería hay proyectos de manipulación remota como lo son la manipulación de robots, procesos de ensamblado, tambien existen áreas dedicadas al desarrollo de prototipos virtuales. Todas estas aplicaciones facilitan la automatización dentro de diferentes áreas.Manipulación remota de robots Es claro que los robots dan una gran aportación a los procesos de ensamblado de la industria. El agregar la característica de manipulación desde un lugar remoto abre las posibilidades para el mejoramiento de este tipo de procesos, puesto que se puede tener un robot que realice proceso definidos y donde su manipulación sea dada desde un lugar distinto de donde se encuentra físicamente. Las aplicaciones forman parte un nuevo enfoque del manejo de procesos y refleja las nuevas tendencias actuales, donde los lugares se vuelven más cercanos y la distancia deja de ser un issue a considerar. Éste proyecto es un tipo de realidad inmersiva.
Realidad Digital en la Oceanología Utilizando la realidad virtual en proyectos de oceanología se puede visualizar una estructura tridimensional de la superificie del oceáno, donde se puede modelar por ejemplo el comportamiento de larvas, tener una simulación de cómo el viento afecta las olas, u observar fenómenos como los de El Niño La Niña, observando temperaturas, dirección de vientos velocidad.
Realidad digital en museos y planetariosLa realidad digital juega un papel importante para el conocimiento, es utilizada por museos, planetarios y centros de ciencia. Estos centros realizan exposiciones virtuales donde se pueden hacer recorridos en templos antiguos, palacios, galaxias, aprender de diversas áreas de conocimiento, entre otras. En algunos de los proyectos realizados en los centros, se experimenta con situaciones más cotidianas con las que los visitantes (principalmente los jovenes y niños) pueden identificarse, for example, se puede diseñar una montaña rusa(roller coaster) y posteriormente experimentar el viaje como si físicamente se estuviera en la montaña, así, mientras se disfruta del viaje se puede aprender de leyes de física. Otro de los enfoques que se le da a la realidad virtual, es el de experimentar visitas virtuales a lugares templos antiguos que por alguna razón no están disponibles al usuario (destrucción, restauración).
Algunos de los enfoques más comunes que los arquitectos dan al uso de realidad digital es en el modelado virtual de sus diseños de casas y edificios, donde además de hacer los diseños tradicionales como planos y maquetas elaboran un modelo tridimensional interactivo, donde sus clientes pueden contemplar de una manera másactuallos diseños inclusive adentrarse en estos edificios casas y recorrerlos libremente, teniendo así una visión mas clara de las ideas que se tratan de expresar.
Los usos actuales más frecuentes de la realidad digital son los siguientes:
Entrenamiento de pilotos, astronautas, soldados, and so on…
Medicina educativa, por ejemplo para la simulacion de operaciones
CAD (diseños asistido por ordenador). Permite ver e interactuar con objetos antes de ser creados, con el evidente ahorro de costes.
Creación de entornos digital (museos, tiendas, aulas, and many others…).
Tratamiento de fobias. (aerofobia, aracnofobia, claustrofobia, and so forth..)
Juegos, Cine 3D y todo tipo de entretenimiento.
Para visión
La realidad digital en el área de la visión trabaja básicamente con dos tipos de implementos: cascos y growth, este último es un equipo que consiste en un brazo mecánico que sostiene un show a través del cual al girarlo se puede observar el entorno del mundo virtual en el cual se está; debido a que su peso es soportado por el brazo mecánico y no por el usuario, como ocurre con el casco, este puede ser un equipo de mayor complejidad y contenido electrónico, lo cual se traduce en ventajas tales como la obtención de una mejor solución.
Características de estos equipos para visión:
Visión estereoscópica:
Es la sensación de ver una determinada imagen en 3 dimensiones, esto se logra haciendo una representación igual para cada ojo de la imagen que se va a observar, estas representaciones son posteriormente proyectadas desde un mismo plano y separadas una distancia que está determinada por la distancia a la cual se encuentra el observador del plano de las imágenes. Desde este punto de vista, también existen equipos de visión monocular a través de los cuales se visualizan los objetos en la forma routine.
Son equipos que constan de una pantalla individual para cada ojo, para el funcionamiento de la visión estereoscópica, es necesario tener un equipo que tenga esta característica; para equipos de visión monoscópica esta característica es opcional. Likewise, también existen equipos monoculares, los cuales constan de una sola pantalla para ambos ojos.
Para interactuar
En la actualidad la realidad digital esta haciendo uso de guantes y vestidos como medio para interactuar en un ambiente digital, para lograr esto, estos dispositivos se comportan inicialmente como dispositivos de entrada que le permiten al computador conocer la ubicación del usuario dentro del ambiente virtual, así mismo, le permiten al usuario ubicarse en el medio e interactuar con el y en algunos casos recibir ciertos estímulos donde estos dispositivos se convierten en dispositivos de salida.
Algunas sensaciones estímulos que se pueden recibir son:
Sensación de estar sosteniendo un objeto que se ha cogido dentro del ambiente digital:
Esto se logra gracias a unas almohadillas que se inflan en el guante y dan la sensación de percibir un peso.
También se puede llegar a percibir la rugosidad y forma propias de objetos situados en el interior del ambiente digital:
Lo cual se logra gracias a que algunos dispositivos tienen partes de aleaciones con memoria que tras variaciones en la temperatura toman formas que se les han practicado con anterioridad.
Para audición
Los audífonos son el equipo básico empleado para escuchar los sonidos propios de un ambiente virtual.
Variantes de estos equipos para adicionar:
Audífonos convencionales:
Son los audífonos de uso más corriente, a través de estos se escucha el sonido simulado de los objetos sin identificar auditivamente el punto de ubicación del mismo.
El Visiocasco: (El usuario se lo coloca en la cabeza)
Este Visiocasco te impide lo que te rodea. Poniéndote una pantalla en cada ojo. Las imágenes que aparecen en las dos pantallas son ligeramente diferentes, de forma que el efecto es que el usuario puede ver un relieve.
Un mando con botones:
Apretando el botón se desplazará en la dirección en la que en ese momento esté mirando.
Un sensor de posición (está en el visiocasco)
Para identificar dónde está viendo, el cual está conectado a la unidad de control, mide tu posición.
Tanto el visiocasco como el mando de control están conectados a una computadora.
Existen siete mecanismos habitualmente empleados en las aplicaciones de la realidad digital. These are:
Gráficos tridimensionales (3D):
Técnicas de estereoscopia:
Esta técnica permite al usuario no solo percibir las claves de la profundidad, sino además ver la imagen en relieve. Esto se debe a que la imagen que percibe cada ojo es algo distinta lo que le permite al cerebro comparar las dos imágenes y deducir, a partir de las diferencias relativas.
Simulación de comportamiento:
La simulación en el mundo digital no está pre calculada la evolución, esta se va calculando en tiempo actual.
Facilidades de navegación:
Es el dispositivo de management, que te permite indicar lo que quieres navegación, esto realiza a través de un joystick de las teclas de control del computador también se puede cuando mueves la cabeza, en ese momento el sistema detecta el hecho y desplaza la imagen de la pantalla.
Técnicas de inmersión:
Consisten en aislarte de los estímulos del mundo actual, al quedar privado de sensaciones procedentes del mundo real, pierdes la referencia con la cual puedes comparar las sensaciones que el mundo digital produce.
Trajes Virtuales:
Consisten en reproducir los estimulos por medio de un traje de latex que trasmite impulsos eléctricos simulando la realidad creada y dando al sentido de tacto la percepción de que lo digital es actual.
Viajes Virtuales:
Consisten en aislarte de los estímulos del mundo real y sumergirse totalmente en interfases virtuales, donde recibes estimulos visuales, auditivos y de movimiento que hacen vivir la VR como una expresión actual y de aprendizaje múltiple, muchas veces el usurario puede ser casi separado de lo real y hacer que lo que viva en VR sea su realidad construida.
En un sistema de realidad digital se pueden distinguir elementos hardware y elementos software.
Los componentes hardware más importantes son el computador, los periféricos de entrada y los periféricos de salida.
Los componentes software más importantes son el modelo geométrico 3Dy los programas de simulación sensorial (simulación visual, auditiva, táctil, ), simulación física (movimiento de la cámara virtual, detección de colisiones, cálculo de deformaciones, ), y recogida de datos. La siguiente figura ilustra los componentes de un sistema típico de realidad digital:
A continuación describiremos brevemente cada uno de estos componentes:
Periféricos de entrada (sensors)
Los periféricos de entrada se encargan de capturar las acciones del participante y enviar esta información al computador. Los periféricos de entrada más frecuentes en realidad digital son los posicionadores (que permiten al sistema conocer en tiempo real la posición y la orientación de la cabeza, de la mano, de todo el cuerpo del usuario), los guantes (que permiten detectar movimiento de los dedos de la mano) y los micrófonos (que graban la voz del participante).
Periféricos de salida (efectores)
Los periféricos de salida se encargan de traducir las señales de audio, video, and so forth. generados por el computador en estímulos para los órganos de los sentidos (sonido, imagery, ). Los efectores se clasifican según el sentido al que va dirigido: existen efectores visuales (cascos estereoscópicos, pantallas de proyección, ), y de audio (sistemas de sonido, altavoces, ) de fuerza y tacto (dispositivos táctiles), y del sentido del equilibrio (plataformas móviles).
El computador se encarga de llevar a cavo la simulación de forma interactiva, basándose en el modelo geométrico 3D y en el software program de recogida de datos, simulación física y simulación sensorial. Debido a que el proceso más crítico en realidad virtual es la simulación visible (síntesis de imágenes a partir de modelos 3D), los computadores que se utilizan para realidad digital son estaciones de trabajo con prestaciones gráficas avanzadas, donde la mayor parte de las etapas del proceso de visualización están implementadas por hardware.
Modelo geométrico 3D
Dado que un sistema de realidad digital tiene que permitir explorar la escena de forma interactiva y ver el mundo digital desde cualquier punto de vista, es necesario disponer de una representación geométrica 3D de este mundo, que permita hacer los cálculos de imágenes, generación de sonido espacial, cálculo de colisiones, etc. a los módulos que describiremos más adelante.
Software program de tratamiento de datos de entrada
Los módulos de recogida y tratamiento de datos se encargan de leer y procesar la información que proporcionan los sensores. Esto incluye los controladores de los dispositivos físicos, así como los módulos para el primer tratamiento de los datos suministrados. For example, los datos de posición y orientación de la cabeza del usuario normalmente se tienen que transformar para expresarlas en un sistema de coordenadas de la aplicación y se deben filtrar para evitar saltos repentinos como consecuencia de lecturas erróneas de los valores de posición. Los sistemas que permiten la comunicación con el ordenador mediante órdenes orales requieren un sistema de reconocimiento de voz. Otros sistemas utilizan un esquema de comunicación basado en gestos de la mano (una especie de lenguaje de sordo-mudos pero más sencillo) y que requiere el reconocimiento de gestos a partir de una secuencia de movimientos.
Software de simulación física
Los módulos de simulación física se encargan de llevar a cabo las modificaciones pertinentes en la representación digital de la escena, a partir de las acciones del usuario y de la evolución interna del sistema. For example, si el módulo de recogida de datos indica que el usuario tiene que hacer el gesto correspondiente a abrir una puerta, el sistema debe aplicar la transformación geométrica correspondiente al objeto del modelo 3D que representa esta puerta. Estos módulos varían mucho dependiendo de la aplicación concreta. La función más básica consiste en calcular en tiempo actual los parámetros de la cámara virtual de acuerdo con los movimientos del usuario, aunque también puede encargarse del cálculo de colisiones, deformaciones, comportamiento y otras actualizaciones que afecten a la evolución en el tiempo del entorno virtual representado.
Software program de simulación sensorial
Estos módulos se encargan de calcular la representación digital de las imágenes, sonidos, and so forth. que el hardware se encargará de traducir a señales y finalmente a estímulos para los sentidos. Entre los módulos de simulación sensorial, lo más importante es el de simulación visual, que se basa en algoritmos de visualización en tiempo real del modelo geométrico. Los algoritmos de visualización que se utilizan en realidad digital son parecidos a los que se han descrito en los capítulos anteriores pero, dado que el rendimiento es crítico, se utilizan técnicas de aceleración de imagen con el propósito de reducir al mínimo posible el tiempo de generación de cada fotograma. Respecto a la simulación auditiva, es preciso comentar que la generación de sonido realista requiere tener en cuenta las propiedades acústicas de los objetos y que los algoritmos son tan complicados como los algoritmos de visualización. Respecto a la simulación táctil, es necesario distinguir entre los dispositivos que proporcionan sensación de tacto (a menudo limitado a la mano), sensación de contacto (también limitado a la mano) y realimentación de fuerza (impiden u ofrecen resistencia a hacer movimientos con la mano cuando ésta choca virtualmente con un objeto virtual). In any case, es imprescindible que el sistema sea capaz de detectar en tiempo actual las colisiones que se puedan producir entre la mano del usuario y los objetos de la escena, ya que es esto evento el que activa los dispositivos hardware apropiado.
Una modelo anuncia ropa interior en el panel publicitario de una parada de autobús. Una usuaria se acerca, presiona sobre la imagen y la pantalla le muestra en un mapa dónde está la tienda más cercana para comprar esas prendas. Es un ejemplo de realidad aumentada, un sistema que consigue incorporar información virtual a la realidad mediante la superposición de capas de datos relacionados con una imagen preexistente. Estas técnicas ya se utilizan como complementos educativos en visitas a museos, pero también en sistemas militares y en procedimientos médicos; en arquitectura como easy entretenimiento. Ahora aterrizan en los móviles.
Con el fin de poder aplicar soluciones de realidad aumentada se necesitan aparatos específicos, como pantallas transparentes y táctiles, gafas especiales teléfonos móviles. En un futuro cercano, However, se podrán utilizar aplicaciones de realidad aumentada dentro de una lente de contacto. Esto abrirá la puerta a numerosos servicios y aplicaciones publicitarias para el consumidor, más cercanas a la ciencia ficción que a la tecnología punta actual.
No en vano películas del género como ‘Minority Reporthan permitido descubrir en la gran pantalla los posibles usos de los sistemas de realidad aumentada, antes incluso de que estos sistemas estuvieran disponibles en el mercado. La escena en la que el actor Tom Cruise recibe en su ojo publicidad personalizada a medida que pasa ante los paneles es prueba de ello.
La realidad aumentada (RA) es el término que se usa para definir una visión directa indirecta de un entorno físico del mundo real, cuyos elementos se combinan con elementos virtuales para la creación de una realidad mixta en tiempo real. Consiste en un conjunto de dispositivos que añaden información digital a la información física ya existente, I mean, añadir una parte sintética virtual a lo real. Esta es la principal diferencia con la realidad digital, puesto que no sustituye la realidad física, sino que sobreimprime los datos informáticos al mundo actual.
Con la ayuda de la tecnología (for example, añadiendo la visión por computador y reconocimiento de objetos) la información sobre el mundo real alrededor del usuario se convierte en interactiva y digital. La información artificial sobre el medio ambiente y los objetos pueden ser almacenada y recuperada como una capa de información en la parte superior de la visión del mundo actual.
La realidad aumentada de investigación explora la aplicación de imágenes generadas por ordenador en tiempo real a secuencias de vídeo como una forma de ampliar el mundo real. La investigación incluye el uso de pantallas colocadas en la cabeza, un show virtual colocado en la retina para mejorar la visualización, y la construcción de ambientes controlados a partir sensores y actuadores.
Con el paso de los años, estudiantes y profesores de todos los niveles han encarado un problema preocupante: algunas áreas de la educación son difíciles de asimilar y de enseñar. En busca de solución a este problema, en los últimos años se ha incrementado el interés en una importante rama de la computación que fue creada en los sesenta y desarrollada desde finales de los ochenta, llamadaRealidad Virtual”, “RV”.
En efecto, la realidad digital tiene importantes aplicaciones en la educación en normal pues hay indicios de que estimula de manera considerable el proceso de aprendizaje a través del llamado efecto deinmersiónque genera la computadora y gracias al cual los estudiantes pueden interactuar completamente con un ambiente artificial utilizando los sentidos del tacto, el oído, y la vista por medio de aparatos especiales que están conectados a la computadora, tales comoguantes de datosy pequeños monitores de video dentro de un casco (fotografía 1).
Estos aparatos tienen sensores que detectan el movimiento en forma precisa, repercutiendo en el mundo virtual en el que los estudiantes interactúan. El ciberespacio es también utilizado en RV, este concepto engloba a los mundos virtuales y a la Web, constituye un espacio en el que los usuarios pueden almacenar los mundos virtuales e intercambiar información, en el ciberespacio, donde pueden actuar como participantes activos. Gracias a elementos como estos, los estudiantes pueden aprender prácticamente cualquier área del conocimiento utilizando esta tecnología.
En la actualidad en el Perú funcionan cerca de 70 universidades y existen gran cantidad de expedientes presentados a CONAFU, para solicitar la autorización de funcionamiento de universidades a lo largo y ancho del Perú.
Nuestras universidades tratan de cubrir la angustiante necesidad de profesionalización en amplios sectores de la juventud peruana, pero lo único verdadero que hacen es encubrir el desempleo juvenil, ya que estos al egresar, después de más de cinco años de preparación, se encuentran con una realidad monda y lironda: No hay Empleo”
Por la preparación deficiente y porque muchas de estas universidades al ser manejadas como un negocio cualquiera, cuyos fines son el lucro, su producto social”, sus egresados, no son lo debidamente competitivos para poder ubicarse dentro del mercado de trabajo.
La proliferación de universidades privadas en el Perú ha generado todo un advertising de posicionamiento de éstas por lograr la mayor población estudiantil dentro de los diferentes segmentos A, B, C y D de los estratos poblacionales.
Las universidades en el Perú deberían considerar que su producto social: sus egresados, deben estar preparados y competitivos para desenvolverse en un mundo tecnológico, donde el cambio y donde los conceptos de educación, preparación, formación y de valores están velozmente cambiando.
Las universidades en el Perú, si bien son transmisoras del conocimiento, ya no son los únicos. Definitivamente la Universitas” deben interrelacionarse con el sector productivo de la nación para que estén adecuadas a la realidad.
No quedan dudas sobre el impacto del fenómeno de la globalización en las relaciones humanas y en las transacciones de todo tipo, pero paradójicamente; hasta ahora la educación es el único sector que ha resistido frontal y tenazmente a la globalización.
No existe una educación international”, se siguen defendiendo actitudes localistas, centralizadoras y cuando se proponen modificaciones en los programas de educación para integrar las nuevas tecnologías digitales, las mismas autoridades, por razones de una no entendida tecnofobia, buscan que todo cambie para que nada cambie”. El acceso masivo a la educación es un fenómeno positivo en sí mismo pero que no asegura calidad de ésa.
El tema del presente artículo es como la educación digital, con la utilización de sus prótesis tecnológicas sirve para unir el proceso educativo al mundo.
La tecnología se desarrolla a una velocidad tan grande que es difícil determinar sus rumbos, su calidad y sus aplicaciones educativas. Por otro lado la educación se mueve tan lentamente que la brecha entre la tecnología y el proceso educativo se hace cada día más amplia
Las nuevas tecnologías electrónicas han creado soportes verdaderamente prodigiosos para transmitir todo tipo de información que eran inimaginables hace una década en el campo de la educación, la adecuación de estas formas a los contenidos educativos es aún demasiado lenta por no decir nula.
Según la UNESCO a la fecha han existido cinco duplicaciones del conocimiento humano, desde que apareció el Hombre en la tierra; en la actualidad los conocimientos científicos y técnicos se multiplican por dos aproximadamente cada cinco años y en el siguiente milenio (por los años 2020) se estima que cada 73 días el conocimiento aumentará el doble.
En contraposición de la realidad concreta física se encuentra la realidad digital. La realidad concreta puede ser percibida por todos los sentidos: view, ear, olfato, tacto y gusto. Mientras que la realidad digital solo puede ser percibida por la vista y el oído en algunos casos y por la conciencia en otros.
Las diferentes formas de la realidad digital son:
to) La simulación por computadoras:
Esta modalidad se consigue mediante la generación por ordenador de un conjunto de imágenes que son contempladas por el usuario a través de un casco provisto de un visor especial. Algunos equipos se completan con trajes y guantes equipados con sensores diseñados para simular la percepción de diferentes estímulos, que intensifican la sensación de realidad. Su aplicación, aunque centrada inicialmente en el terreno de los videojuegos, se ha extendido a otros muchos campos, como la medicina, simulación de vuelo, and many others.
b) Las pantallas de televisor y de cine:
Con una tecnología menos complicada y mas al alcance de la gente las imágenes, videos y películas nos ofrecen una realidad virtual sencilla y en dos dimensiones.
c) La imaginación y la cromnesia:
Sin el uso de tecnología alguna y siempre a mano nuestra mente nos ofrece un universo repleto de formas, colores, sonidos, olores, sabores y sensaciones táctiles. Esto para la imaginación. A través de la cromnesia nosotros podemos percibir y representar el tiempo y la duración. Esto no lo ofrece ninguna tecnología diseñada hasta ahora.
El poder de la imaginación es tal que cuando un sujeto imagina una acción se activan las mismas regiones cerebrales que cuando realmente la realiza. Los deportistas son los que mejor conocen este poder desde hace tiempo. Se puede entrenar mentalmente, poner en funcionamiento las actitudes adecuadas y afinar reflejos repitiendo solo mentalmente la futura prueba.
La realidad concreta está constituida por diversas cualidades características las cuales generan en el cerebro las sensaciones correspondientes. Con la realidad digital se separan y se manejan esas características para producir un efecto de realidad.
El futuro no está escrito, pero es seguro que las comunidades virtuales conquistarán mayores y mejores conocimientos tecnológicos. Si en los próximos años el ciberespacio se utiliza con mayor eficacia, es posible que supere en todas sus dimensiones al universo actual actual. Todo ello cambiará la vida de los humanos en muchos aspectos.
En un futuro no muy lejano, existirán decorados virtuales en los que los actores se moverían como en un escenario real, obteniendo respuesta en tiempo actual de los objetos del atrezzo digital, evitando así construirlos realmente.
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