Essentials of Artificial IntelligenceSince its publication, Essentials of Artificial Intelligence has beenadopted at numerous universities and colleges offering introductory AIcourses at the graduate and undergraduate levels. Based on the author'scourse at Stanford University, the book is an integrated, cohesiveintroduction to the field. The author has a fresh, entertaining writingstyle that combines clear presentations with humor and AI anecdotes. At thesame time, as an active AI researcher, he presents the materialauthoritatively and with insight that reflects a contemporary, first handunderstanding of the field. Pedagogically designed, this book offers arange of exercises and examples. |
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action algorithm applied approach Artificial Intelligence assigned assumptions ATMS axiom backtracking big(h binding bird(x birds branching factor breadth-first search certainty factor chapter color conclusion conditional independence conjunction consider database decide default theory depth depth-first search derive described discussed domain edge examine example expected expert system explanation fact first-order logic flies(x Fred function Ginsberg given goal node heuristic Hobbes idea influence diagram initial node instance involves John knowledge representation label language learning Mary metalevel modus ponens move MYCIN nonmonotonic reasoning noun object ostriches parse planning possible pr(p probabilistic probability theory proof prove quantified query q resolution resolve result rule search problem search space semantic semantic net sentence shown in Figure simply solution solve specific subclass subset Suppose techniques theorem things ticket tree Turing test Tweety typically variable verb words work(h