Artificial Intelligence: Modern Approach by Stuart J. Russell, Peter Norvig
By Stuart J. Russell, Peter Norvig
A hugely available, up to date expert reference for programmers, software program engineers, approach directors, or technical managers, this e-book integrates cutting-edge AI innovations into clever agent designs utilizing examples and workouts to steer the reader from basic reactive brokers to complete knowledge-based brokers with typical language features.
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Additional info for Artificial Intelligence: Modern Approach
It it now almost taken for granted among many psychologists that "a cognitive theory should be like a computer program" (Andersen, 1980). By this it is meant that the theory should describe cognition as consisting of well-definej transformation processes operating at the level of the information carried by the input signals. For most of the early history of AI and cognitive science, no significant distinction was drawn between the two fields, and it was common to see AI programs described as psychological 9 William James was the brother of novelist Henry James.
A reduction is a general transformation from one class of problems to another, such that solutions to the first class can be found by reducing them to problems of the second class and solving the latter problems. NP COMPLETENESS How can one recognize an intractable problem? The theory of NP-completeness, pioneered by Steven Cook (1971) and Richard Karp (1972), provides a method. Cook and Karp showed the existence of large classes of canonical combinatorial search and reasoning problems that are NP-complete.
The more formal theory of decisions is discussed in the following section. 7 In this picture, all meaningful statements can be verified or falsified either by analyzing the meaning of the words or by carrying out experiments. Because this rules out most of metaphysics, as was the intention, logical positivism w a s unpopular in some circles. 2. The Foundations of Artificial Intelligence 11 Mathematics (c. 800-present) Philosophers staked out most of the important ideas of AI, but to make the leap to a formal science required a level of mathematical formalization in three main areas: computation, logic, ALGORITHM and probability.