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The Soar Cognitive Architecture.

By: Contributor(s): Material type: TextTextSeries: The MIT Press SeriesPublisher: Cambridge : MIT Press, 2012Copyright date: ©2012Edition: 1st edDescription: 1 online resource (391 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780262301145
Subject(s): Genre/Form: Additional physical formats: Print version:: The Soar Cognitive ArchitectureDDC classification:
  • 006.3
LOC classification:
  • Q335 -- .L329 2012eb
Online resources:
Contents:
Intro -- Contents -- Preface -- Acknowledgments -- Chapter 1. Introduction -- 1.1 Background -- 1.2 Cognitive Architectures -- 1.3 Soar -- 1.4 Research Strategy -- 1.5 Preview of Chapters 2-14 -- Chapter 2. Requirements for Cognitive Architectures -- 2.1 Characteristics of Environments, Tasks, and Agents -- 2.2 Architectural Requirements -- Chapter 3. The Problem-Space Computational Model -- 3.1 Task Environments -- 3.2 The Problem-Space Framework -- 3.3 Knowledge Search -- 3.4 Problem-Space Computational Models -- 3.5 Impasses and Substates -- 3.6 Using Multiple Sources of Knowledge -- 3.7 Acquiring Knowledge -- 3.8 Alternative PSCMs -- Chapter 4. Soar as an Implementation of the PSCM -- 4.1 Production Systems -- 4.2 Mapping Production Systems onto the PSCM -- 4.3 The Soar Processing Cycle -- 4.4 Demonstrations of Basic PSCM -- 4.5 Discussion -- 4.6 Analysis of Requirements -- Chapter 5. Impasses and Substates: The Basis for Complex Reasoning -- 5.1 Impasses -- 5.2 Substates -- 5.3 Problem Solving in Substates -- 5.4 Substate Results -- 5.5 Maintaining Consistency -- 5.6 Demonstrations of Impasses and Substates -- 5.7 Discussion -- 5.8 Analysis of Requirements -- Chapter 6. Chunking -- 6.1 Chunking in Soar -- 6.2 Implications of Chunking in Soar -- 6.3 Demonstrations of Chunking -- 6.4 Assumptions Inherent to Chunking -- Chapter 7. Tuning Procedural Knowledge: Reinforcement Learning -- 7.1 Reinforcement Learning in Soar -- 7.2 Learning over Large State Spaces -- 7.3 Demonstrations of Reinforcement Learning -- 7.4 Analysis of Requirements -- Chapter 8. Semantic Memory -- 8.1 Semantic Memory in Soar -- 8.2 Encoding and Storage -- 8.3 Retrieval -- 8.4 Demonstrations of Semantic Memory -- 8.5 Analysis of Requirements -- Chapter 9. Episodic Memory -- 9.1 Episodic Memory in Soar -- 9.2 Encoding and Storage -- 9.3 Retrieval.
9.4 Use of Episodic Memory -- 9.5 Demonstrations of Episodic Memory -- 9.6 Comparison of Episodic Memory and Semantic Memory -- 9.7 Analysis of Requirements -- Chapter 10. Visuospatial Processing with Mental Imagery -- 10.1 Visual and Spatial Representations -- 10.2 Visuospatial Domains -- 10.3 SVS -- 10.4 Demonstrations of Spatial and Visual Imagery -- 10.5 Analysis of Requirements -- Chapter 11. Emotion -- 11.1 Appraisal Theories of Emotion -- 11.2 Abstract Functional Cognitive Operations -- 11.3 Unifying Cognitive Control and Appraisal -- 11.4 Emotion, Mood, and Feeling -- 11.5 Emotion and Reinforcement Learning -- 11.6 Demonstrations of Emotion Processing -- 11.7 Analysis of Requirements -- Chapter 12. Demonstrations of Multiple Architectural Capabilities -- 12.1 Learning to Use Episodic Memory with Reinforcement Learning -- 12.2 Using Mental Imagery with Reinforcement Learning -- 12.3 Diverse Forms of Action Modeling -- 12.4 Analysis of Requirements -- Chapter 13. Soar Applications -- 13.1 Applications -- 13.2 TacAir-Soar -- 13.3 Imagining TacAir-Soar 2.0 -- Chapter 14. Conclusion -- 14.1 Soar from a Structural Perspective -- 14.2 Soar from a Functional Perspective -- 14.3 Evaluating Soar on Architectural Requirements -- References -- Index.
Summary: The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components.
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Intro -- Contents -- Preface -- Acknowledgments -- Chapter 1. Introduction -- 1.1 Background -- 1.2 Cognitive Architectures -- 1.3 Soar -- 1.4 Research Strategy -- 1.5 Preview of Chapters 2-14 -- Chapter 2. Requirements for Cognitive Architectures -- 2.1 Characteristics of Environments, Tasks, and Agents -- 2.2 Architectural Requirements -- Chapter 3. The Problem-Space Computational Model -- 3.1 Task Environments -- 3.2 The Problem-Space Framework -- 3.3 Knowledge Search -- 3.4 Problem-Space Computational Models -- 3.5 Impasses and Substates -- 3.6 Using Multiple Sources of Knowledge -- 3.7 Acquiring Knowledge -- 3.8 Alternative PSCMs -- Chapter 4. Soar as an Implementation of the PSCM -- 4.1 Production Systems -- 4.2 Mapping Production Systems onto the PSCM -- 4.3 The Soar Processing Cycle -- 4.4 Demonstrations of Basic PSCM -- 4.5 Discussion -- 4.6 Analysis of Requirements -- Chapter 5. Impasses and Substates: The Basis for Complex Reasoning -- 5.1 Impasses -- 5.2 Substates -- 5.3 Problem Solving in Substates -- 5.4 Substate Results -- 5.5 Maintaining Consistency -- 5.6 Demonstrations of Impasses and Substates -- 5.7 Discussion -- 5.8 Analysis of Requirements -- Chapter 6. Chunking -- 6.1 Chunking in Soar -- 6.2 Implications of Chunking in Soar -- 6.3 Demonstrations of Chunking -- 6.4 Assumptions Inherent to Chunking -- Chapter 7. Tuning Procedural Knowledge: Reinforcement Learning -- 7.1 Reinforcement Learning in Soar -- 7.2 Learning over Large State Spaces -- 7.3 Demonstrations of Reinforcement Learning -- 7.4 Analysis of Requirements -- Chapter 8. Semantic Memory -- 8.1 Semantic Memory in Soar -- 8.2 Encoding and Storage -- 8.3 Retrieval -- 8.4 Demonstrations of Semantic Memory -- 8.5 Analysis of Requirements -- Chapter 9. Episodic Memory -- 9.1 Episodic Memory in Soar -- 9.2 Encoding and Storage -- 9.3 Retrieval.

9.4 Use of Episodic Memory -- 9.5 Demonstrations of Episodic Memory -- 9.6 Comparison of Episodic Memory and Semantic Memory -- 9.7 Analysis of Requirements -- Chapter 10. Visuospatial Processing with Mental Imagery -- 10.1 Visual and Spatial Representations -- 10.2 Visuospatial Domains -- 10.3 SVS -- 10.4 Demonstrations of Spatial and Visual Imagery -- 10.5 Analysis of Requirements -- Chapter 11. Emotion -- 11.1 Appraisal Theories of Emotion -- 11.2 Abstract Functional Cognitive Operations -- 11.3 Unifying Cognitive Control and Appraisal -- 11.4 Emotion, Mood, and Feeling -- 11.5 Emotion and Reinforcement Learning -- 11.6 Demonstrations of Emotion Processing -- 11.7 Analysis of Requirements -- Chapter 12. Demonstrations of Multiple Architectural Capabilities -- 12.1 Learning to Use Episodic Memory with Reinforcement Learning -- 12.2 Using Mental Imagery with Reinforcement Learning -- 12.3 Diverse Forms of Action Modeling -- 12.4 Analysis of Requirements -- Chapter 13. Soar Applications -- 13.1 Applications -- 13.2 TacAir-Soar -- 13.3 Imagining TacAir-Soar 2.0 -- Chapter 14. Conclusion -- 14.1 Soar from a Structural Perspective -- 14.2 Soar from a Functional Perspective -- 14.3 Evaluating Soar on Architectural Requirements -- References -- Index.

The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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