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 |
453 | |
493 | |
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Common terms and phrases
achieve action agent algorithm applied arcs Artificial Intelligence atom axioms backed-up value Bayes network block branching factor breadth-first breadth-first search calculate called cell chapter clause Clear Fl Clear(B condition conditional independencies conjunction constraints CPTs d-separation data structure denoted depth depth-first search described discussion effects environment evaluation example expert systems expression False formulas given goal node graph heuristic Horn clauses inference input vectors joint probability knowledge base labeled language learning LIFTABLE literals logic machines methods move objects On(A On(B On(C operators optimal path output polytree positive instances preconditions predicate calculus probabilistic inference problem procedure produce PROLOG propositional calculus quantifier reasoning represent representation resolution refutation robot scene search tree semantic sensory shown in Figure sigmoid sigmoid function situation calculus STRIPS rules successors Suppose symbols T-R programs techniques terminal symbols training set truth table value True variables