Human and Machine Problem Solving
Problem solving is a central topic for both cognitive psychology and artificial intelligence (AI). Psychology seeks to analyze naturally occur ring problem solving into hypothetical processes, while AI seeks to synthesize problem-solving performance from well-defined processes. Psychology may sugge...
Other Authors: | |
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Format: | eBook |
Language: | English |
Published: |
New York, NY
Springer US
1989, 1989
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Edition: | 1st ed. 1989 |
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Online Access: | |
Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 10. Example of Implementation Method for Chess
- 11. Knowledge-Based Selective Search
- 12. Exact Play in Chess Endgames
- 13. Other Nonprobabilistic Games
- 14. Games of Imperfect Information, Game Theory
- 15. Conclusion—Likely Future Trends
- 16. References
- 17. Further Reading
- 5 Adversary Problem Solving by Humans
- 1. Adversary Games
- 2. Dealing with the Adversary
- 3. Characteristics of the Search Process
- 4. Plans and Knowledge
- 5. Evaluation Functions
- 6. Projecting Ahead
- 7. Humans versus Computers
- 8. Overview
- 9. References
- 6 Machine Expertise
- 1. The Automation of Problem Solving—Continuing a Tradition
- 2. Problem-Solving Knowledge Representation
- 3. The Nature of Expert Knowledge
- 4. Knowledge Representation
- 5. Problems with the Traditional Approach
- 6. Architectures for Representing MachineExpertise
- 7. The Rule-Based Approach—mycin, prospector, and xcon
- 8. The Blackboard Approach (hearsay)
- 9. The Set-Covering Approach (Frame Abduction)
- 10. Multiple Paradigm Approaches
- 11. Expert System Shells
- 12. Recent Developments
- 13. Conclusions
- 14. References
- 7 Human Expertise
- 1. Introduction
- 2. The Theoretical Framework: Information-Processing Theory of Problem Solving
- 3. The Construction of a Problem Representation
- 4. The Role of Schemata in Problem Solving
- 5. Problem-Solving Strategies
- 6. The Development of Expertise
- 7. Conclusion
- 8. References
- 8 Machine Inference
- 1. Input of Knowledge
- 2. Machine Inference Based on Logic
- 3. The Production-Rule-Based Approach to Inference
- 4. The Frame-Based Approach to Inference
- 5. The Current Status of Machine Inference
- 6. References
- 9 Human Inference
- 1. Introduction
- 2. The Mental Logic Approach
- 3. The Mental Models Approach
- 4. The Nature of Inference
- 5. References
- 10 Machine Learning
- 1. Introduction
- 2. Learning Concepts from Examples: Problem Statement
- Author Index
- 1 Human and Machine Problem Solving: Toward a Comparative Cognitive Science
- 1. Introduction
- 2. Problem Solving
- 3. Perspectives
- 4. Some Issues
- 5. References
- 2 Nonadversary Problem Solving by Machine
- 1. Introduction
- 2. State Space Representation
- 3. Problem Reduction Representation: And/or Graphs
- 4. Planning
- 5. Conclusions
- 6. References
- 3 Human Nonadversary Problem Solving
- 1. Introduction
- 2. Constraints on a Model of Human Nonadversary Problem Solving
- 3. Conclusion
- 4. References
- 4 Adversary Problem Solving by Machine
- 1. Introduction
- 2. Search Techniques for Two-Person Games
- 3. Minimaxing with an Evaluation Function
- 4. The Alpha-Beta Algorithm
- 5. Refinements of the Basic Alpha-Beta Rule
- 6. Theoretical Analyses of Alpha-Beta and Its Variants
- 7. Other Problem-Independent Adversary Search Methods
- 8. Selective Search, Evaluation Functions, and Quiescence
- 9. A Short History of Game-Playing Programs
- 3. Learning Concepts by Induction: A Detailed Example
- 4. Learning Decision Trees and Coping with Noise
- 5. Other Approaches to Learning and Bibliographical Remarks
- 6. References
- 11 Human Learning
- 1. Introduction
- 2. Schemata, Scripts, and Frames
- 3. Amnesia
- 4. Retrieval from Long-Term Memory
- 5. Concept Learning
- 6. Conclusions
- 7. References
- 12 Problem Solving by Human-Machine Interaction
- 1. Problem Solving for the Real World
- 2. Problem Solving Reconsidered from a Human Factors Perspective
- 3. Stages of the Problem-Solving Process
- 4. Human-Computer Problem Solving: Cases
- 5. A Retrospective Example
- 6. Summary and Conclusions
- 7. References
- 8. Further Reading
- 13 Human and MachineProblem Solving: A Comparative Overview
- 1. Introduction
- 2. Nonadversary Problems
- 3. Adversary Problems
- 4. Expertise
- 5. Inference
- 6. Learning
- 7. Solving Problems by Human-Computer Interaction
- 8. Concluding Comments
- 9. References