Computer Sciences Dept.

Fuzzy Planner: Computing Inexactness in a Procedural Problem-Solving Language

Rob Kling

All contemporary deductive problem-solving paradigms deal with a world in which assertions are true (false) and action-rules valid (invalid). This simplified situation is inadequate for realistic applications which include inexact information. This report describes a precise computationally specific method for coupling two different many-valued logic with a procedural problem-solving system (PLANNER). Solutions to deductive problems can be found which meet specific criteria of validity. This particular scheme enables the system to dynamically compute the truth- value of a subgoal during the search process. Thus, the validity of a subgoal may be used to direct the heuristic search procedure. Fuzzy PLANNER is a promising medium for experimenting with different many-valued logics to find the ones, most appropriate for different problem domains.

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