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Understanding intelligence

Front Cover
2 Reviews
MIT Press, 2001 - Computers - 697 pages

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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Review: Understanding Intelligence

User Review  - Uwe Hauck - Goodreads

A really good overview on current research in Artificial Intelligence, expecially embodie AI. Read full review

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Selected pages

Contents

The Study of Intelligence
3
11 Characterizing Intelligence
6
The Synthetic Approach
21
Foundations of Classical Artificial Intelligence and Cognitive Science
35
22 The Cognitivistic Paradigm
39
23 An Architecture for an Intelligent Agent
47
The Fundamental Problems of Classical Artificial Intelligence and Cognitive Science
59
32 Some WellKnown Problems with Classical Systems
63
103 Design Principles in Context
318
The Principle of Parallel Loosely Coupled Processes
327
111 Control Architectures for Autonomous Agents
330
112 Traditional Views on Control Architectures
337
113 Parallel Decentralized Approaches
345
A SelfSufficient Garbage Collector
357
The Principle of SensoryMotor Coordination
377
Traditional Approaches
378

33 The Fundamental Problems
64
34 Remedies and Alternatives
74
A Framework for Embodied Cognitive Science
79
Embodied Cognitive Science Basic Concepts
81
41 Complete Autonomous Agents
82
42 Biological and Artificial Agents
99
43 Designing for EmergenceLogicBased and Embodied Systems
111
44 Explaining Behavior
127
Neural Networks for Adaptive Behavior
139
51 From Biological to Artificial Neural Networks
140
52 The Four or Five Basics
143
53 Distributed Adaptive Control
152
54 Types of Neural Networks
167
A Polemic Digression
172
Approaches and Agent Examples
179
Braitenberg Vehicles
181
62 The Fourteen Vehicles
182
63 Segmentation of Behavior and the Extended Braitenberg Architecture
195
The Subsumption Architecture
199
71 BehaviorBased Robotics
201
72 Designing a SubsumptionBased Robot
202
73 Examples of SubsumptionBased Architectures
206
The Subsumption Approach to Designing Intelligent Systems
219
Artificial Evolution and Artificial Life
227
81 Basic Principles
230
Evolving a Neural Controller for an Autonomous Agent
234
83 Examples of Artificially Evolved Agents
240
Cell Growth form GenomeBased CelltoCell Communication
250
85 Real Robots Evolution of Hardware and Simulation
255
Additional Examples
260
87 Methodological Issues and Conclusions
270
Other Approaches
277
92 Behavioral Economics
283
93 SchemaBased Approaches
292
Principles of Intelligent Systems
297
Design Principles of Autonomous Agents
299
102 Design Principles for Autonomous Agents
302
122 The SensoryMotor Coordination Approach
392
The SMC Agents
407
Active Vision
431
The Principles of Cheap Design Redundancy and Ecological Balance
435
132 The Redundancy Principle
446
133 The Principle of Ecological Balance
455
The Value Principle
467
141 Value Systems
469
142 SelfOrganization
475
143 Learning in Autonomous Agents
485
A Case Study
503
152 Problems of Classical Notions of Memory
506
153 The FrameofReference Problem in Memory Research
511
154 Alternatives
516
155 Implications for Memory Research
530
Design and Evaluation
535
Agent Design Considerations
537
161 Preliminary Design Considerations
539
162 Agent Design
542
Control Architectures
562
164 Summary and a Fundamental Issue
569
Evaluation
577
171 The Basics of Agent Evaluation
578
172 Performing Agent Experiments
588
173 Measuring Behavior
593
Future Directions
605
Theory Technology and Applications
607
182 Theory and Technology
612
183 Applications
618
Intelligence Revisited
631
192 Implications for Society
638
Glossary
645
References
659
Author Index
677
Subject Index
681
Copyright

Common terms and phrases

achieved action activation Adaptive agent's behavior algorithms approach artificial evolution artificial intelligence autonomous agents avoid-obstacle basic brain Braitenberg vehicles cell changes chapter charging station cheap design classical collision complete agent complex connections control architecture design principles desired behaviors discussed dynamics ecological balance ecological niche embodied agents embodied cognitive science emergent evolutionary evolved example experiments exploited figure finite state machines focus function goal Hebbian learning human idea implemented information processing input interaction internal involved issues large number layer loosely coupled processes low-level specification machine mechanisms memory module motor system move natural neural networks neurons nodes object obstacle ontology output particular perspective physical problem psychology real robots real world redundancy reinforcement learning result self-organization sensors sensory-motor coordination signals simple simulation structure subsumption architecture supervised learning task environment term thinking tion Turing turn types value system visual

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References from web pages

Understanding Intelligence - The MIT Press
He is the author of Understanding Intelligence (MIT Press, 1999). ... "Understanding Intelligence is a comprehensive and highly readable introduction to ...
mitpress.mit.edu/ book-home.tcl?isbn=0262161818

Understanding Intelligence
Understanding Intelligence. Rolf Pfeifer and Christian Scheier. Copyright 2002 Erina Thomas. Do you have any comments about this site? ...
www.ifi.unizh.ch/ groups/ ailab/ people/ pfeifer/ undint.html

Acta Psychologica : Rolf Pfeifer and Christian Scheier (1999 ...
What Understanding Intelligence does try to do is satisfy our demand for a ... The strategy of the writers of Understanding Intelligence in this chapter is ...
linkinghub.elsevier.com/ retrieve/ pii/ S000169180000041X

<I>Understanding Intelligence</I> by Rolf Pfeifer and Christian ...
Understanding Intelligence by Rolf Pfeifer and Christian Scheier, MIT Press, price £37. 50, ISBN 0262161818 IF YOU want to understand how a machine works,
technology.newscientist.com/ channel/ tech/ robots/ mg16622335.600

<b>UNDERSTANDING INTELLIGENCE, </b>by Rolf Pfeifer and Christian ...
UNDERSTANDING INTELLIGENCE, by Rolf Pfeifer and Christian Scheier, MIT Press, Cambridge, Mass., 1999, xx&plus;697 pp. ISBN 0-262-16181-8 (hardback, £37.50). ...
portal.acm.org/ citation.cfm?id=980357.980369

American Journal of Psychiatry -- FORREST 157 (12): 2074
Understanding Intelligence. by Rolf Pfeifer and Christian Scheier. Cambridge, Mass., MIT Press, 1999, 697 pp., $63.00. DAVID V. FORREST, md New York, ny ...
ajp.psychiatryonline.org/ cgi/ content/ full/ 157/ 12/ 2074

COGNITIVE SCIENCE:If You Build It, Will It Know? -- Markman 288 ...
Understanding Intelligence Rolf Pfeifer and Christian Scheier ... Understanding Intelligence is a comprehensive and highly readable introduction to embodied ...
www.sciencemag.org/ cgi/ content/ full/ sci;288/ 5466/ 624

Foundations and Problems of Traditional Artificial Intelligence
55 Ch. 2, Understanding Intelligence, Pfeifer, Scheier 1999. Fundamental problems chapter 3 - Understanding Intelligence Pfeifer 1999. General problems: ...
www.aisland.org/ cki20/ media/ foundations_and_problems_AI.pps

Dawson Margin Notes On
Dawson Margin Notes On. Pfeifer and Scheier, Understanding Intelligence. Chapter 4: Embodied Cognitive Science: Basic Concepts ...
www.bcp.psych.ualberta.ca/ ~mike/ Pearl_Street/ Margin/ Pfeifer/ chap4.html

ingentaconnect Simple environments fail as illustrations of ...
Simple environments fail as illustrations of intelligence: A review of R. Pfeifer and C. Scheier, Understanding Intelligence*. Authors: Lane pcr1; Gobet F. ...
www.ingentaconnect.com/ content/ els/ 00043702/ 2001/ 00000127/ 00000002/ art00063;jsessionid=3hgggh48pq9e4.alice?format=print

About the author (2001)

Christian Scheier is a Postdoctoral Fellow at the California Institute of Technology, Pasadena, California.

Bibliographic information

QR code for Understanding intelligence
TitleUnderstanding intelligence
Bradford Books
AuthorsRolf Pfiefer, Scheier (Christian)
Editionillustrated, reprint
PublisherMIT Press, 2001
ISBN0262250799, 9780262250795
Length697 pages
Subjects › 

Computers / Intelligence (AI) & Semantics
Science / General
  
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