Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development
IEEE Transactions on Software Engineering - Special issue on artificial intelligence and software engineering
The structure-mapping engine: algorithm and examples
Artificial Intelligence
Learning by understanding analogies (reasoning)
Learning by understanding analogies (reasoning)
Formulating concepts and analogies according to purpose
Formulating concepts and analogies according to purpose
A reactive approach to explanation in expert and advice-giving systems
A reactive approach to explanation in expert and advice-giving systems
Planning text for advisory dialogues
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
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The ability to generate descriptive explanations of domain concepts defined in a knowledge base is an important requirement for any system with explanatory capabilities. The ability to use analogies to highlight selected features in the description of the concept greatly enhances the possibility of the system being able to convey its point to the user. In this paper, we shall describe a system designed within the EES framework that embodies this capability. Finding analogies is not simple, but we shall show how the utterance discourse structure can provide the system with additional knowledge that can aid finding an acceptable analogy to express. Analogies are a powerful and compact means of communicating ideas and descriptions. Using analogies in language generation is different from using analogies in problem solving. This paper will outline some of these differences and demonstrates one attempt at incorporating them within an expert system that generates explanations for its users in natural language.