Nils Nilsson�s long and rich research career has contributed much to AI. His previous books, often considered
classics in the field, include Learning Machines, Problem-Solving Methods in Artificial Intelligence, Logical Foundations
of Artificial Intelligence, and 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.
Summary
Intelligent agents are employed as the central characters in this new 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. The book provides a refreshing and motivating new synthesis of the field by one of AI's master
expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour
of this intriguing new world of AI.
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
1 Introduction
2 Stimulus-Response Agents
3 Neural Networks
4 Machine Evolution
5 State Machines
6 Robot Vision
7 Agents that Plan
8 Uninformed Search
9 Heuristic Search
10 Planning, Acting, and Learning
11 Alternative Search Formulations and Applications
12 Adversarial Search
13 The Propositional Calculus
14 Resolution in The Propositional Calculus
15 The Predicate Calculus
16 Resolution in the Predicate Calculus
17 Knowledge-Based Systems
18 Representing Commonsense Knowledge
19 Reasoning with Uncertain Information
20 Learning and Acting with Bayes Nets
21 The Situation Calculus
22 Planning
23 Multiple Agents
24 Communication Among Agents
25 Agent Architectures
