Artificial Intelligence

• covers different ways to represent these functions, such as production systems, reactive agents, logical planners and decision- theoretic systems
• explains the role of learning as extending the reach of the designer into unknown environments, and shows how it constrains agent design, favoring explicit knowledge representation and reasoning
• includes a thorough, up-to-date and integrated treatment of robotics and vision, written by John Canny and Jitendra Malik, two of the leading exponents in their respective fields
• analyzes basic techniques for addressing complexity (use of approximation, compilation, anytime algorithms, hierarchical abstraction) as general sources of power

Tackles AI's philosophical critics head-on.

Gives equal emphasis to theory and practice—considers the basic concepts and mathematical methods of AI, what can and cannot be done with today's technology, at what cost, and using what techniques.

Integrates state-of-the art AI techniques intointelligent agent designs, using examples and exercises to lead the student from simple, reactive agents to full knowledge-based agents with natural language capabilities. Includes over 75 algorithms, and a variety of simulated environments for testing agent designs.

presents algorithms at three levels of detail — prose descriptions and pseudo-code in the text, and complete Common Lisp programs available by anonymous ftp or on floppy disk

Includes numerous written and programming exercises in each chapter.

Contents

I. ARTIFICIAL INTELLIGENCE.

1. Introduction.
2. Intelligent Agents.

II. PROBLEM-SOLVING.

3. Solving Problems by Searching.
4. Informed Search Methods.
5. Game Playing.

III. KNOWLEDGE AND REASONING.

6. Agents that Reason Logically.
7. First-order Logic.
8. Building a Knowledge Base.
9. Inference in First-Order Logic.
10. Logical Reasoning Systems.

IV. ACTING LOGICALLY.

11. Planning.
12. Practical Planning.
13. Planning and Acting.

V. UNCERTAIN KNOWLEDGE AND REASONING.

14. Uncertainty.
15. Probabilistic Reasoning Systems.
16. Making Simple Decisions.
17. Making Complex Decisions.

VI. LEARNING.

18. Learning from Observations.
19. Learning with Neural Networks.
20. Reinforcement Learning.
21. Knowledge in Learning.

VII. COMMUNICATING, PERCEIVING, AND ACTING.

22. Agents that Communicate.
23. Practical Communication in English.
24. Perception.
25. Robotics.

VIII. CONCLUSIONS.

26. Philosophical Foundations.
27. AI: Present and Future.