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Artificial and Computational Intelligence

Artificial intelligence is both the intelligence of machines and the branch of computer science which aims to create it. The term artificial intelligence is also used to describe a property of machines or programs: the intelligence that the system demonstrates. AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory, probability, optimization and logic.

Subjects in computational intelligence as defined by IEEE Computational Intelligence Society mainly include: Neural networks: trainable systems with very strong pattern recognition capabilities. Fuzzy systems: techniques for reasoning under uncertainty, have been widely used in modern industrial and consumer product control systems; capable of working with concepts such as ‘hot’, ‘cold’, ‘warm’ and ‘boiling’. Evolutionary computation: applies biologically inspired concepts such as populations, mutation and survival of the fittest to generate increasingly better solutions to the problem

AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others. Computational intelligence Computational intelligence involves iterative development or learning (e.g., parameter tuning in connectionist systems).

Major AI textbooks define artificial intelligence as “the study and design of intelligent agents, where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. John McCarthy, who coined the term in 1956, defines it as “the science and engineering of making intelligent machines.

Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. General intelligence (or “strong AI”) has not yet been achieved and is a long-term goal of some AI research.

AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, ontology, operations research, economics, control theory, probability, optimization and logic. AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others.

“Artificial intelligence is the next stage in evolution,” Edward Fredkin said in the 1980s, expressing an idea first proposed by Samuel Butler’s Darwin Among the Machines (1863), and expanded upon by George Dyson in his book of the same name (1998). Several futurists and science fiction writers have predicted that human beings and machines will merge in the future into cyborgs that are more capable and powerful than either. This idea, called transhumanism, has roots in Aldous Huxley and Robert Ettinger, is now associated with robot designer Hans Moravec, cyberneticist Kevin Warwick and Ray Kurzweil.

 

Retrieved 20th August 2008 at 18:29

*Science daily, http://www.sciencedaily.com/articles/a/artificial_intelligence.htm

*http://en.wikipedia.org/wiki/Artificial_intelligence

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agosto 20, 2008 - Posted by | Human Language Technologies |

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