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Hunting for Assumptions as Developing Method for Problem-Solving Methods

Published: 1997 August

Buchtitel: Workshop Proceedings Problem-solving Methods for Knowledge-based Systems in Connection with the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI'97), Nagoya, Japan, August 23-25, 1997

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Problem-solving methods (PSMs) for knowledge-based systems need to make assumptions to provide effective and efficient problem solving: assumptions about the scope of the problem they should solve and assumptions about the domain knowledge they can use as a resource for their reasoning process. If these assumptions are made explicit they can improve the reusability of PSMs by guiding the selection and refinement process of problem-solving methods for a given application and by defining goals for the acquisition process of domain knowledge. However, making the underlying assumptions explicit is not an easy task. The goal of our paper is to contribute to solve this problem. The main idea is to construct mathematical proofs and analysis of their failure as a systematic means for forming assumptions. Tool support is provided by adapting the Karlsruhe Interactive Verifier (KIV) for our purpose. KIV is an interactive theorem prover that returns with open goals if a proof could not be completed. These open goals can be used to derive the assumptions we are looking for.

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