Adapting Propositional Cases Based on Tableaux Repairs Using Adaptation Knowledge
Adaptation is a step of case-based reasoning that aims at modifying a source case (representing a problem-solving episode) in order to solve a new problem, called the target case. An approach to adaptation consists in applying a belief revision operator that modifies minimally the source case so that it becomes consistent with the target case. Another approach consists in using domain-dependent adaptation rules. These two approaches can be combined: a revision operator parametrized by the adaptation rules is introduced and the corresponding revision-based adaptation uses the rules to modify the source case. This paper presents an algorithm for revision-based and rule-based adaptation based on tableaux repairs in propositional logic: when the conjunction of source and target cases is inconsistent, the tableaux method leads to a set of branches, each of them ending with clashes, and then, these clashes are repaired (thus modifying the source case), with the help of the adaptation rules. This algorithm has been implemented in the Revisor/PLAK tool and some implementation issues are presented.
KeywordsCase-based reasoning adaptation tableaux repairs propositional logic belief revision adaptation rules
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