Artificial Intelligence: Structures and Strategies for Complex Problem SolvingThis 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. |
Contents
PARTI | 1 |
PART II | 29 |
STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH | 75 |
Copyright | |
17 other sections not shown
Common terms and phrases
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 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 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 requires result returns s-expression search algorithm Section semantic networks sentence setf setq slot solution solver space search specific stack strategies stream substitutions symbol syntax techniques theorem theory tion training instances tree true unification unify variable verb