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List of contents
Part 1. Multiple Environments and Multiple Contexts in Knowledge Engineering. 1. Introducing Multi-Environmental and Multi-Context Knowledge-Based Systems: A New Approach. 2. What is a Multiple Environment and How Does It Affect the Function of a Knowledge-Based System? 3. A Framework for Transfer of Expert Systems Between Environments. 4. Impact of Multiple Environments on the Functioning of Medical and Other Knowledge-Based Systems. 5. Activity Structures: A Methodology for Design of Multi-Environment and Multi-Context Knowledge-Based Systems. Part 2. Methods of Knowledge Elicitation. 6. Knowledge Elicitation – An Exercise in Identification and Verification of Expert Knowledge. 7. Knowledge Elicitation – The First Step Towards the Construction of Expert Systems: The Outline of a Method. 8. Linking Argumentative Discourse with Formal Evaluation Procedures in Design. 9. Problems of Knowledge Elicitation in Insurance. Part 3. Design of Knowledge-Based Systems and Robots for Multi-Environmental Situations. 10. An Overview of Clinaid. 11. Design of Questioning Strategies for Knowledge-Based Systems. 12. Concurrency in Clinaid. 13. Distributed Architectures for Computer Aided Manufacturing (CAM) and Other Embedded Robotic Systems. 14. Towards a Design of a Real-Time Adaptive Robot for Multiple Environments: Part I – Basic Design and the First Experiments. 15. The Design of the House as a System in Multi-Environmental Space. Part 4. Method for Design Validation of Multi-Environmental Knowledge-Based Systems. 16. The Use of Fuzzy Relational Products in Comparison and Verification of Correctness of Knowledge Structures. 17. Development of the Support Tools and Methodology for Design and Validation of Multi-Environmental Computer Architectures. Part 5. Epilogue. 18. Knowledge as a Confidential Marketable Commodity: Cultural Danger or Economic Blessing?
About the author
Ladislav J. Kohout, John Anderson, Wyllis Bandler
Summary
First published in 1992, this volume identifies the problems facing the designer of multi-environmental knowledge-based systems, and explains the principles that must be followed in order to obtain successful results.
