本书是一本经典的人工智能教材，全面阐述了人工智能的基础理论，有效结合了求解智能问题的数据结构以及实现的算法，把人工智能的应用程序应用于实际环境中，并从社会和哲学、心理学以及神经生理学角度对人工智能进行了独特的讨论。

PART Ⅰ

ARTIFICIAL INTELLIGENCE:ITS ROOTS AND SCOPE 1

1 AI:HISTORY AND APPLICATONS

PART Ⅱ

ARTIFICIAL INTELLIGENCE AS REPRESENTATION AND SEARCH

2 THE PREDICATE CALCULUS

3 STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH

4 HEURISTIC SEARCH

5 STOCHASTIC METHODS

6 CONTROL AND IMPLEMENTATION OF STATE SPACE SEARCH

PART Ⅲ

CAPTURING INTELLIGENCE:THE AI CHALLENGE

7 KNOWLEDGE REPRESENTATION

8 STRONG METHOD PROBLEM SOLVING

9 REASONING IN UNCERTAIN SITUATIONS

PART Ⅳ

MACHINE LEARNING

10 MACHINE LEARNING:SYMBOL-BASED

11 MACHINE LEARNING:CONNECTIONIST

12 MACHINE LEARNING:GENETIC AND EMERGENT

13 MACHINE LEARNING:PROBABILISTIC

PART Ⅴ

ADVANCED TOPICS FOR AI PROBLEM SOLVING

14 AUTOMATED REASONING

15 UNDERSTANDING NATURAL LANGUAGE

PART Ⅵ

EPILOGUE

16 ARTIFICIAL INTELLIGENCE AS EMPIRICAL ENQUIRY