Description Table of Contents Details Authors

Description

Intelligent 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.

Key Features

An evolutionary approach provides a unifying theme Thorough coverage of important AI ideas, old and new Frequent use of examples and illustrative diagrams Extensive coverage of machine learning methods throughout the text Citations to over 500 references Comprehensive index

Table of Contents

Reactive Machines. Neural Networks. Machine Evolution. State Machines. Robot Vision. Search in State Spaces. Agents that Plan. Uninformed Search. Heuristic Search. Planning, Acting and Learning. Alternative Search. Knowledge Representation and Reasoning. The Propositional Calculus. The Predicate Calculus. Knowledge-based Systems. Representing Common sense Knowledge. Reasoning with Uncertain Information. Learning and Acting with Bayes Nets. Planning Methods Based on Logic. The Situation Calculus. Planning. Communication and Integration. Multiple Agents. Communication Among Agents. Agent Architectures.

Details

No. of pages:
513
Language:
English
Copyright:
© 1997
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9780080948348
Print ISBN:
9781558605350

About the author

Nils Nilsson

Nils J. Nilsson's long and rich research career has contributed much to AI. He has written many books, including the classic Principles of Artificial Intelligence. Dr. Nilsson is Kumagai Professor of Engineering, Emeritus, at Stanford University. He has served on the editorial boards of Artificial Intelligence and Machine Learning and as an Area Editor for the Journal of the Association for Computing Machinery. Former Chairman of the Department of Computer Science at Stanford, and former Director of the SRI Artificial Intelligence Center, he is also a past president and Fellow of the American Association for Artificial Intelligence.

Affiliations and Expertise

Stanford University
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