The Soar cognitive architecture /:
The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. ; London, England :
MIT Press,
©2012.
©2012 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. |
| Beschreibung: | "A Bradford Book." |
| Beschreibung: | 1 online resource (xv, 374 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780262301145 0262301148 1280499273 9781280499272 |
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| 100 | 1 | |a Laird, John, |d 1954- | |
| 245 | 1 | 4 | |a The Soar cognitive architecture / |c John E. Laird. |
| 260 | |a Cambridge, Mass. ; |a London, England : |b MIT Press, |c ©2012. | ||
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| 500 | |a "A Bradford Book." | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 520 | |a The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a Chapter 4. Soar as an Implementation of the PSCM4.1 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 | |
| 505 | 8 | |a 6.3 Demonstrations of Chunking6.4 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 | |
| 505 | 8 | |a 9.5 Demonstrations of Episodic Memory9.6 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 | |
| 505 | 8 | |a 11.6 Demonstrations of Emotion Processing11.7 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 | |
| 650 | 0 | |a Artificial intelligence. |0 http://id.loc.gov/authorities/subjects/sh85008180 | |
| 650 | 0 | |a Software architecture. |0 http://id.loc.gov/authorities/subjects/sh2004001071 | |
| 650 | 2 | |a Artificial Intelligence |0 https://id.nlm.nih.gov/mesh/D001185 | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 6 | |a Architecture logicielle. | |
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| 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 PSCM4.1 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 Chunking6.4 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 Memory9.6 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 Processing11.7 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 |
| ctrlnum | (OCoLC)793207181 |
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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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Chapter 4. Soar as an Implementation of the PSCM4.1 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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6.3 Demonstrations of Chunking6.4 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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">9.5 Demonstrations of Episodic Memory9.6 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</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">11.6 Demonstrations of Emotion Processing11.7 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. 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| id | ZDB-4-EBU-ocn793207181 |
| illustrated | Illustrated |
| indexdate | 2024-11-26T14:49:05Z |
| institution | BVB |
| isbn | 9780262301145 0262301148 1280499273 9781280499272 |
| language | English |
| oclc_num | 793207181 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xv, 374 pages) : illustrations |
| psigel | ZDB-4-EBU |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | MIT Press, |
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| spelling | Laird, John, 1954- The Soar cognitive architecture / John E. Laird. Cambridge, Mass. ; London, England : MIT Press, ©2012. ©2012 1 online resource (xv, 374 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file rda "A Bradford Book." Includes bibliographical references and index. Print version record. The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. 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 PSCM4.1 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 Chunking6.4 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 Memory9.6 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 Processing11.7 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 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Software architecture. http://id.loc.gov/authorities/subjects/sh2004001071 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Intelligence artificielle. Architecture logicielle. artificial intelligence. aat COMPUTERS Enterprise Applications Business Intelligence Tools. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Artificial intelligence fast Software architecture fast COMPUTER SCIENCE/General COGNITIVE SCIENCES/General has work: The Soar cognitive architecture (Text) https://id.oclc.org/worldcat/entity/E39PCH3wRHKxdJxtqX8wKp6YKb https://id.oclc.org/worldcat/ontology/hasWork Print version: Laird, John, 1954- Soar cognitive architecture. Cambridge, Mass. : MIT Press, ©2012 9780262122962 0262122960 (DLC) 2011030567 (OCoLC)748290725 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=449838 Volltext |
| spellingShingle | Laird, John, 1954- The Soar cognitive architecture / 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 PSCM4.1 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 Chunking6.4 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 Memory9.6 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 Processing11.7 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 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Software architecture. http://id.loc.gov/authorities/subjects/sh2004001071 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Intelligence artificielle. Architecture logicielle. artificial intelligence. aat COMPUTERS Enterprise Applications Business Intelligence Tools. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Artificial intelligence fast Software architecture fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85008180 http://id.loc.gov/authorities/subjects/sh2004001071 https://id.nlm.nih.gov/mesh/D001185 |
| title | The Soar cognitive architecture / |
| title_auth | The Soar cognitive architecture / |
| title_exact_search | The Soar cognitive architecture / |
| title_full | The Soar cognitive architecture / John E. Laird. |
| title_fullStr | The Soar cognitive architecture / John E. Laird. |
| title_full_unstemmed | The Soar cognitive architecture / John E. Laird. |
| title_short | The Soar cognitive architecture / |
| title_sort | soar cognitive architecture |
| topic | Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Software architecture. http://id.loc.gov/authorities/subjects/sh2004001071 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Intelligence artificielle. Architecture logicielle. artificial intelligence. aat COMPUTERS Enterprise Applications Business Intelligence Tools. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Artificial intelligence fast Software architecture fast |
| topic_facet | Artificial intelligence. Software architecture. Artificial Intelligence Intelligence artificielle. Architecture logicielle. artificial intelligence. COMPUTERS Enterprise Applications Business Intelligence Tools. COMPUTERS Intelligence (AI) & Semantics. Artificial intelligence Software architecture |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=449838 |
| work_keys_str_mv | AT lairdjohn thesoarcognitivearchitecture AT lairdjohn soarcognitivearchitecture |