Cover Image
Read Now

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...

Full description

Bibliographic Details
Other Authors: Gilhooly, K.J. (Editor)
Format: eBook
Language:English
Published: New York, NY Springer US 1989, 1989
Edition:1st ed. 1989
Subjects:
Computer Science
Cognitive Psychology
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

Similar Items