About the author
Nils J. Nilsson's long and rich research career has contributed much to Al. His previous books,
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
Joumal of the Association for Computing Machinery. Former chairman of the Department of
Computer Science at Stanford and Former Director of the SRl Artificial Intelligence Center, he is
also a past president and fellow of the American Association for Artificial Intelligence.

1 Introduction
I Reactive Machines
2 Stimulus-Response Agents
3 Neural Networks
4 Machine Evolution
5 State Machines
6 Robot Vision
II Search in State Spaces
7 Agents That Plan
8 Uninformed Search
9 Heuristic Search
10 Planning, Acting, and Learning
11 Alternative Search Formulations and Applications
12 Adversarial Search
III Knowledge Representation and Reasoning
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
IV Planning Methods Based on Logic
21 The Situation Calculus
22 Planning
V Communication and Integration
23 Multiple Agents
24 Communication among Agents
25 Agent Architectures