Understanding Intelligence


By the mid-1980s researchers from artificial intelligence, computer science, brain and cognitive science, and psychology realized that the idea of computers as intelligent machines was inappropriate. The brain does not run "programs"; it does something entirely different. But what? Evolutionary theory says that the brain has evolved not to do mathematical proofs but to control our behavior, to ensure our survival. Researchers now agree that intelligence always manifests itself in behavior—thus it is behavior that we must understand. An exciting new field has grown around the study of behavior-based intelligence, also known as embodied cognitive science, "new AI," and "behavior-based AI."

This book provides a systematic introduction to this new way of thinking. After discussing concepts and approaches such as subsumption architecture, Braitenberg vehicles, evolutionary robotics, artificial life, self-organization, and learning, the authors derive a set of principles and a coherent framework for the study of naturally and artificially intelligent systems, or autonomous agents. This framework is based on a synthetic methodology whose goal is understanding by designing and building.

The book includes all the background material required to understand the principles underlying intelligence, as well as enough detailed information on intelligent robotics and simulated agents so readers can begin experiments and projects on their own. The reader is guided through a series of case studies that illustrate the design principles of embodied cognitive science.

Table of Contents

  1. Preface
  2. I. The Study of Intelligence—Foundations and Issues
  3. 1. The Study of Intelligence
  4. 2. Foundations of Classical Artificial Intelligence and Cognitive Science
  5. 3. The Fundamental Problems of Classical Artificial Intelligence and Cognitive Science
  6. II. A Framework for Embodied Cognitive Science
  7. 4. Embodied Cognitive Science: Basic Concepts
  8. 5. Neural Networks for Adaptive Behavior
  9. III. Approaches and Agent Examples
  10. 6. Braitenberg Vehicles
  11. 7. The Subsumption Architecture
  12. 8. Artificial Evolution and Artificial Life
  13. 9. Other Approaches
  14. IV. Principles of Intelligent Systems
  15. 10. Design Principles of Autonomous Agents
  16. 11. The Principle of Parallel, Loosely Coupled Processes
  17. 12. The Principle of Sensory. Motor Coordination
  18. 13. The Principles of Cheap Design, Redundancy, and Ecological Balance
  19. 14. The Value Principle
  20. 15. Human Memory: a Case Study
  21. V. Design and Evaluation
  22. 16. Agent Design Considerations
  23. 17. Evaluation
  24. VI. Future Directions
  25. 18. Theory, Technology, and Applications
  26. 19. Intelligence Revisited
  27. Glossary
  28. References
  29. Author Index
  30. Subject Index