Artificial Intelligence: A New SynthesisIntelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches.

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Contents
Chapter 1 Introduction  1 
Reactive Machines  19 
Search in State Spaces  115 
Knowledge Representation and Reasoning  215 
Planning Methods Based on Logic  361 
Communication and Integration  405 
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achieve action agent algorithm applied arcs Artiﬁcial Artificial Intelligence atom axioms backedup value Bayes network block branching factor calculate called cell chapter clause Clear(B condition conditional independencies conjunction constraints dseparation data structure deﬁned deﬁnition denoted depth depthﬁrst described discussion effects environment evaluation example expert systems expression False ﬁnd ﬁnding ﬁrst ﬂoor formulas given goal node graph heuristic Horn clauses inference input vectors joint probability knowledge base labeled language learning literals logic machines methods move objects On(A On(B operators optimal path output polytree positive instances preconditions predicate calculus predicatecalculus probabilistic inference problem procedure produce PROLOG propositional calculus quantiﬁer reasoning represent representation resolution refutation robot satisﬁed scene search tree semantic sensory shown in Figure sigmoid sigmoid function situation calculus speciﬁc STRIPS rules successors Suppose symbols TR programs techniques terminal symbols training set truth table value True variables weight