Journal of the ACM (JACM)
Linear resolution for consequence finding
Artificial Intelligence
A goal-dependent abstraction for legal reasoning by analogy
Artificial Intelligence and Law
Concept Formation and Knowledge Revision
Concept Formation and Knowledge Revision
Constructing predicate mappings for goal-dependent abstraction
Annals of Mathematics and Artificial Intelligence
Explanation-Based Generalization: A Unifying View
Machine Learning
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This paper proposes a new framework of knowledge revision, called Similarity-Driven Knowledge Revision. Our revision is invoked based on a similarity observation by users and is intended to match with the observation. Particularly, we are concerned with a revision strategy according to which an inadequate variable typing in describing an object-oriented knowledge base is revised by specializing the typing to more specific one without loss of the original inference power. To realize it, we introduce a notion of extended sorts that can be viewed as a concept not appearing explicitly in the original knowledge base. If a variable typing with some sort is considered over-general, the typing is modified by replacing it with more specific extended sort. Such an extended sort can efficiently be identified by forward reasoning with SOL-deduction from the original knowledge base. Some experimental results show the use of SOL-deduction can drastically improve the computational efficiency.