It includes Appendix, Exercises, Bibliography, Index and Colophon

This book explains how it is possible for computers to reason and perceive, thus introducing the field called artificial intelligence. This book would appeal to programmers, professionals and students. This completely rewritten and updated edition reflects the revolutionary progress made since the previous edition was published.

Table of Content
Acknowledgements
Software
Preface
Representations and Methods
The Intelligent Computer
Semantic Nets and Description Matching
Generate and Test, Means-Ends Analysis, and Problem Reduction
Nets and Basic Search
Nets and Optimal Search
Trees and Adversarial Search
Rules and Rule Chaining
Rules, Substrates, and Cognitive Modeling
Frames and Inheritance
Fames and Commonsense
Numeric Constraints and Propagation
Symbolic Constraints and Propagation
Logic and Resolution Proof
Backtracking and Truth Maintenance
Planning
Learning and Regularity Recognition
Learning by Analyzing Difference
Learning by Explaining Experience
Learning by Correcting Mistakes
Learning by Recording Cases
Learning by Managing Multiple Models
Learning by Building Identification Trees
Learning by Training Neural Nets
Learning by Training Perceptions
Learning by Training Approximation Nets
Learning by Simulating Evolution
Recognizing Objects
Describing Images
Expressing Language Constrains
Responding to Questions and Commands
Appendices
Relational Databases
Exercises
Bibliography
Index
Colophon


Salient Features

Semiformal representation and procedure specifications bring the ideas to within a step or two implementation and highlight unifying themes.
Application examples provide a glimpse of the ideas at work in real-world systems.
Powerful ideas and principles are identified ad emphasized.