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Artificial intelligence Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. Major AI researchers and textbooks define this field as "the study and design of intelligent agents", in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955,defines it as "the science and engineering of making intelligent machines". Artificial intelligence, or AI, is the field that studies the synthesis and analysis of computational agents that act intelligently. Let us examine each part of this definition. What is an agent? An agent is something that acts in an environment it does something. Agents include worms, dogs, thermostats, airplanes, robots, humans, companies, and countries. How an agent acts? We are interested in what an agent does; that is, how it acts. We judge an agent by its actions. An agent acts intelligently when •what it does is appropriate for its circumstances and its goals, •it is flexible to changing environments and changing goals, •it learns from experience, and •it makes appropriate choices given its perceptual and computational limitations. An agent typically cannot observe the state of the world directly; it has only a finite memory and it does not have unlimited time to act. Goals: • Deduction, reasoning, problem solving • Knowledge representation •Planning •Learning •Natural language processing (communication) •Perception • Motion and manipulation Approaches •Cybernetics and brain simulation: In the 1940s and 1950s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.[20] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s. Symbolic: When access to digital computers became possible in the middle 1950s, AI research began to explore the possibility that human intelligence could be reduced to symbol manipulation. The research was centered in three institutions: Carnegie Mellon University, Stanford and MIT, and each one developed its own style of research. Statistical: In the 1990s, AI researchers developed sophisticated mathematical tools to solve specific sub problems. These tools are truly scientific, in the sense that their results are both measurable and verifiable, and they have been responsible for many of AI's recent successes. Integrating the approaches Intelligent agent paradigm An intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. The simplest intelligent agents are programs that solve specific problems. More complicated agents include human beings and organizations of human beings (such as firms). The paradigm gives researchers license to study isolated problems and find solutions that are both verifiable and useful, without agreeing on one single approach.