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.
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Embodied Artificial Intelligence: International Seminar, Dagstuhl Castle ...
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The Study of Intelligence
11 Characterizing Intelligence
The Synthetic Approach
Foundations of Classical Artificial Intelligence and Cognitive Science
22 The Cognitivistic Paradigm
23 An Architecture for an Intelligent Agent
The Fundamental Problems of Classical Artificial Intelligence and Cognitive Science
32 Some WellKnown Problems with Classical Systems
103 Design Principles in Context
The Principle of Parallel Loosely Coupled Processes
111 Control Architectures for Autonomous Agents
112 Traditional Views on Control Architectures
113 Parallel Decentralized Approaches
A SelfSufficient Garbage Collector
The Principle of SensoryMotor Coordination
33 The Fundamental Problems
34 Remedies and Alternatives
A Framework for Embodied Cognitive Science
Embodied Cognitive Science Basic Concepts
41 Complete Autonomous Agents
42 Biological and Artificial Agents
43 Designing for EmergenceLogicBased and Embodied Systems
44 Explaining Behavior
Neural Networks for Adaptive Behavior
51 From Biological to Artificial Neural Networks
52 The Four or Five Basics
53 Distributed Adaptive Control
54 Types of Neural Networks
A Polemic Digression
Approaches and Agent Examples
62 The Fourteen Vehicles
63 Segmentation of Behavior and the Extended Braitenberg Architecture
The Subsumption Architecture
71 BehaviorBased Robotics
72 Designing a SubsumptionBased Robot
73 Examples of SubsumptionBased Architectures
The Subsumption Approach to Designing Intelligent Systems
Artificial Evolution and Artificial Life
81 Basic Principles
Evolving a Neural Controller for an Autonomous Agent
83 Examples of Artificially Evolved Agents
Cell Growth form GenomeBased CelltoCell Communication
85 Real Robots Evolution of Hardware and Simulation
87 Methodological Issues and Conclusions
92 Behavioral Economics
93 SchemaBased Approaches
Principles of Intelligent Systems
Design Principles of Autonomous Agents
102 Design Principles for Autonomous Agents
122 The SensoryMotor Coordination Approach
The SMC Agents
The Principles of Cheap Design Redundancy and Ecological Balance
132 The Redundancy Principle
133 The Principle of Ecological Balance
The Value Principle
141 Value Systems
143 Learning in Autonomous Agents
A Case Study
152 Problems of Classical Notions of Memory
153 The FrameofReference Problem in Memory Research
155 Implications for Memory Research
Design and Evaluation
Agent Design Considerations
161 Preliminary Design Considerations
162 Agent Design
164 Summary and a Fundamental Issue
171 The Basics of Agent Evaluation
172 Performing Agent Experiments
173 Measuring Behavior
Theory Technology and Applications
182 Theory and Technology
192 Implications for Society
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Foundations and Problems of Traditional Artificial Intelligence
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Simple environments fail as illustrations of intelligence: A review of R. Pfeifer and C. Scheier, Understanding Intelligence*. Authors: Lane pcr1; Gobet F. ...
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