Understanding Intelligence

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.

Preface

xi

Part I The Study of Intelligence---Foundations and Issues

1

(78)

The Study of Intelligence

3

(32)

Characterizing Intelligence

6

(15)

Studying Intelligence: The Synthetic Approach

21

(14)

Foundations of Classical Artificial Intelligence and Cognitive Science

35

(24)

Cognitive Science: Preliminaries

35

(4)

The Cognitivistic Paradigm

39

(8)

An Architecture for an Intelligent Agent

47

(12)

The Fundamental Problems of Classical Al and Cognitive Science

59

(20)

Real Worlds versus Virtual Worlds

59

(4)

Some Well-Known Problems with Classical Systems

63

(1)

The Fundamental Problems of Classical Al

64

(10)

Remedies and Alternatives

74

(5)

Part II A Framework for Embodied Cognitive Science

79

(100)

Embodied Cognitive Science: Basic Concepts

81

(58)

Complete Autonomous Agents

82

(17)

Biological and Artificial Agents

99

(12)

Designing for Emergence---Logic-Based and Embodied Systems

111

(16)

Explaining Behavior

127

(12)

Neural Networks for Adaptive Behavior

139

(40)

From Biological to Artificial Neural Networks

140

(3)

The Four or Five Basics

143

(9)

Distributed Adaptive Control

152

(15)

Types of Neural Networks

167

(5)

Beyond Information Processing: A Polemic Digression

172

(7)

Part III Approaches and Agent Examples

179

(118)

Braitenberg Vehicles

181

(18)

Motivation

181

(1)

The Fourteen Vehicles

182

(13)

Segmentation of Behavior and the Extended Braitenberg Architecture

195

(4)

The Subsumption Architecture

199

(28)

Behavior-Based Robotics

201

(1)

Designing a Subsumption-Based Robot

202

(4)

Examples of Subsumption-Based Architectures

206

(13)

Conclusions: The Subsumption Approach to Designing Intelligent Systems

219

(8)

Artificial Evolution and Artificial Life

227

(50)

Basic Principles

230

(4)

An Introduction to Genetic Algorithms: Evolving a Neural Controller for an Autonomous Agent

234

(6)

Examples of Artificially Evolved Agents

240

(10)

Toward Biological Plausibility: Cell Growth from Genome-Based Cell-to-Cell Communication

250

(5)

Real Robots, Evolution of Hardware, and Simulation

255

(5)

Artificial Life: Additional Examples

260

(10)

Methodological Issues and Conclusions

270

(7)

Other Approaches

277

(20)

The Dynamical Systems Approach

277

(6)

Behavioral Economics

283

(9)

Schema-Based Approaches

292

(5)

Part IV Principles of Intelligent Systems

297

(238)

Design Principles of Autonomous Agents

299

(28)

The Nature of the Design Principles

299

(3)

Design Principles for Autonomous Agents

302

(16)

Design Principles in Context

318

(9)

The Principle of Parallel, Loosely Coupled Processes

327

(50)

Control Architectures for Autonomous Agents

330

(7)

Traditional Views on Control Architectures

337

(8)

Parallel, Decentralized Approaches

345

(12)

Case Study: A Self-Sufficient Garbage Collector

357

(20)

The Principle of Sensory-Motor Coordination

377

(58)

Categorization: Traditional Approaches

378

(14)

The Sensory-Motor Coordination Approach

392

(15)

Case Study: The SMC Agents

407

(24)

Application: Active Vision

431

(4)

The Principles of Cheap Design, Redundancy, and Ecological Balance

435

(32)

The Principle of Cheap Design

435

(11)

The Redundancy Principle

446

(9)

The Principle of Ecological Balance

455

(12)

The Value Principle

467

(36)

Value Systems

469

(6)

Self-Organization

475

(10)

Learning in Autonomous Agents

485

(18)

Human Memory: A Case Study

503

(32)

Memory Defined

503

(3)

Problems of Classical Notions of Memory

506

(5)

The Frame-of-Reference Problem in Memory Research

511

(5)

The Alternatives

516

(14)

Implications for Memory Research

530

(5)

Part V Design and Evaluation

535

(70)

Agent Design Considerations

537

(40)

Preliminary Design Considerations

539

(3)

Agent Design

542

(20)

Putting It All Together: Control Architectures

562

(7)

Summary and a Fundamental Issue

569

(8)

Evaluation

577

(28)

General Introduction

578

(10)

Performing Agent Experiments

588

(5)

Measuring Behavior

593

(12)

Part VI Future Directions

605

(40)

Theory, Technology, and Applications

607

(24)

Hard Problems

607

(5)

Theory and Technology

612

(6)

Applications

618

(13)

Intelligence Revisited

631

(14)

Elements of a Theory of Intelligence

631

(1)

Implications for Society

631

(14)

Glossary

645

(14)

References

659

(18)

Author Index

677

(4)

Subject Index

681

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Understanding Intelligence

Summary

Table of Contents

Supplemental Materials