Artificial intelligence: structures and strategies for complex problem solving
This successful book provides a balanced perspective on the languages, schools, theories, and applications of Artificial Intelligence. Now in its third edition, Artificial Intelligence contains an expanded presentation of case based reasoning, genetic algorithms, neural nets, agents, and stochastic models of natural language understanding. In addition, the book contains a discussion of emergent computation and artificial-life.
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STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH
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allows applied argument artificial intelligence backtrack behavior best-first search bindings breadth-first search called Chapter clause Common LISP complex concept conceptual graphs cond data base defined definition defun depth-first depth-first search described discussed domain element evaluation example expert system Figure formal frame function goal grammar heuristic hierarchy human implementation important inference rules inheritance input interpreter knowledge base knowledge representation learning LISP logic programming match method modus ponens move MYCIN natural language node noun noun_phrase object object-oriented programming operations parameter parse path pattern possible problem solving procedure production system PROLOG propositional calculus query reasoning recursive represent representation language require result returns s-expression search algorithm Section semantic networks sentence setf setq slot solution solver space search specific strategies stream subgoals substitutions symbol techniques theorem theory tion training instances tree true unification unify variable verb
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Parallel Processing and Parallel Algorithms: Theory and Computation
Seyed H Roosta
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