Contributions to a Computer-Based Theory of Strategies

1. Introduction.- 2. Basic Concepts of Strategies, Decision Making, and Planning.- 3. The Quasi-Optimizer (QO) System.- 3.1. Introduction and Research Objectives.- 3.2. A Brief Survey of Related Work.- 3.3. The Approach.- 3.4. System Modules.- 3.4.1. The QO-1 Module.- 3.4.2. The QO-2 Module.- 3.4.3. The QO-3 Module.- 3.4.4. The QO-4 Module.- 3.4.5. The QO-5 Module.- 3.4.6. The QO-6 Module.- 3.5. The Implementation.- 3.6. Applications.- 3.7. Summary.- 3.8. Acknowledgements.- 4. The Advice Taker/Inquirer (AT/I).- 4.1. Introduction and Research Objectives.- 4.2. The Approach.- 4.2.1. The Learning Phase.- 4.2.2. The Operational Phase.- 4.3. The Implementation.- 4.3.1. The Definition Facility.- 4.3.2. Prototypes.- 4.3.3. Entity Instantiation.- 4.3.4. Production Rules.- 4.3.5. Procedures and Functions.- 4.3.6. The Units of Measurement.- 4.3.7. The Agenda Mechanism.- 4.3.8. The Inference Engine.- 4.3.9. The Current Situation Assessor.- 4.3.10. The Hypothesizer.- 4.3.11. The Historian.- 4.4. Benefits of Using the AT/I.- 4.5. Applications in Assembly Line Balancing and Street Traffic Light Control.- 4.5.1. The Definition of the Assembly Line Balancing Problem.- 4.5.2. The Definition of the Street Traffic Light Control Problem.- 4.6. Summary.- 4.7. Acknowledgements.- 5. The Generalized Production Rule System (GPRS).- 5.1. Introduction and Research Objectives.- 5.2. The Approach.- 5.2.1. Morphs and the Morph-Fitting Program.- 5.2.2. The Knowledge Base.- 5.2.3. The Optimization of the Knowledge Base.- 5.2.4. The Estimation of Values of Hidden Variables.- 5.3. System Modules.- 5.3.1. The GPRS-1 Module.- 5.3.2. The GPRS-2 Module.- 5.3.3. The GPRS-3 Module.- 5.3.4. The GPRS-4 Module.- 5.3.5. The GPRS-5 Module.- 5.3.6. The GPRS-6 Module.- 5.3.7. The Utility Programs.- 5.4. The Implementation.- 5.4.1. A Pattern Search Method for Optimization.- 5.4.2. The Interaction with the System.- 5.5. Applications.- 5.6. Summary.- 5.7. Acknowledgements.- 6. Distributed Planning and Problem Solving Systems (DPPSS).- 6.1. Introduction and Research Objectives.- 6.1.1. Traditional Al Approaches to Centralized Planning.- 6.1.2. On Distributed Planning and Problem Solving.- 6.1.3. General Categories of Application of DPPSS.- 6.1.4. The Four Phases of Network Activity within DPPSS.- 6.1.5. A Few Major Issues with DPPSS.- 6.1.6. Other Dimensions of Classification of Distributed Planning.- 6.1.7. Global Coherence with Decentralized Control.- 6.1.8. The Issue of Time-Criticality.- 6.1.9. Two Successful Approaches to DPPSS.- 6.2. A Distributed System for Air Traffic Control.- 6.2.1. General Issues.- 6.2.2. Our Approach.- 6.2.3. On Coordinator Selection.- 6.2.4. Configuration Diagrams and Tables.- 6.2.5. Connection through Mutual Selection.- 6.2.6. Distributed Scratch Pads and the ‘Self-Heal’ Process.- 6.2.7. Definitions of Incidents, Conflicts, Violations and Space Measures.- 6.2.8. The Kernel Design of the Individual Processors.- 6.2.9. The Mechanism to Ensure Navigational Safety.- 6.2.10. The Priority-Factor and Its Use.- 6.2.11. The Incremental Shallow Planning.- 6.2.12. The Coordinator-Coworker Structure as the Organizational Scheme.- 6.2.13. The Process of Resolving Incidents.- 6.2.14. The Three Organizational Structures to Be Compared.- 6.2.15. The Distributed Air Traffic Control Testbed.- 6.2.16. The Results of Empirical Investigations.- 6.2.17. Conclusions.- 6.2.18. Future Research Directions.- 6.3. A Distributed System for Manufacturing Control.- 6.3.1. Introduction.- 6.3.2. The General Paradigm.- 6.3.3. The Approach.- 6.4. A System for Distributed and Moving Resources and Tasks.- 6.4.1. Introduction.- 6.4.2. A Domain of Application.- 6.4.3. The Approach.- 6.4.4. The Activities at Different Levels.- 6.4.5. The Salient Features of the System.- 6.5. A Distributed System for Street Traffic Light Control.- 6.5.1. Introduction.- 6.5.2. The Approach.- 6.5.3. The Control Strategies.- 6.5.4. The Information Communicated between Controllers.- 6.5.5. Some Notation and Definitions to Be Used with the Rules.- 6.5.6. The Rules to Control the Traffic Light Regime.- 6.5.7. On Scenario Generation.- 6.5.8. The Optimization of the Rule Base.- 6.6. Summary.- 6.7. Acknowledgements.- 7. Causal Modelling Systems (CMS and NEXUS).- 7.1. Introduction and Perspectives on Causation.- 7.1.1. The Philosophical View of Causality.- 7.1.2. The Probabilistic, Statistical and Logical Approaches to Causality.- 7.1.3. The Sociological View of Causality.- 7.1.4. The Psychological View of Causality.- 7.1.5. Causality in Linguistics and in Natural Language Understanding Systems.- 7.1.6. Causality in Artificial Intelligence.- 7.2. The Causal Modelling System CMS.- 7.2.1. Research Objectives.- 7.2.2. The Development of the Causal Model.- 7.2.3. The Operation of CMS.- 7.2.4. Issues of Implementation.- 7.2.5. Applications of CMS.- 7.3. The Causal Modelling System NEXUS.- 7.3.1. Introduction and Research Objectives.- 7.3.2. The Causal Reasoning and Learning Schemas.- 7.3.3. On Knowledge Representation.- 7.3.4. Reasoning in NEXUS.- 7.3.5. Causal Learning in NEXUS.- 7.3.6. Issues of Implementation.- 7.3.7. Areas of Applications.- 7.4. Summary.- 7.5. Acknowledgements.- 8. The Predictive Man-Machine Environment (PMME).- 8.1. Introduction and Research Objectives.- 8.1.1. On Decision Support Systems.- 8.1.2. The Predictive Man-Machine System.- 8.2. The Simulated Air Traffic Control Environment.- 8.2.1. Some Terminology.- 8.2.2. Attempts at the Implementation.- 8.2.3. The Operation.- 8.3. An Evaluation of the Predictive Man-Machine Environment.- 8.3.1. The Experimental Set-Up.- 8.3.2. The Results of Experiments.- 8.4. Summary.- 8.5. Acknowledgements.- 9. Overall Summary.- References.