On the Semantics and Automated Deduction for PLFC, a Logic of Possibilistic Uncertainty and Fuzziness
This work addresses the need for automated reasoning in uncertain and fuzzy domains, but it is incremental as it extends existing possibilistic logic with fuzzy elements.
The paper tackles the formalization and automated deduction for PLFC, a logic combining possibilistic uncertainty with fuzzy constants, by providing a formal semantics, a sound resolution calculus, and a proof procedure with a novel substitution notion, resulting in a many-valued truth-evaluation system instead of boolean.
Possibilistic logic is a well-known graded logic of uncertainty suitable to reason under incomplete information and partially inconsistent knowledge, which is built upon classical first order logic. There exists for Possibilistic logic a proof procedure based on a refutation complete resolution-style calculus. Recently, a syntactical extension of first order Possibilistic logic (called PLFC) dealing with fuzzy constants and fuzzily restricted quantifiers has been proposed. Our aim is to present steps towards both the formalization of PLFC itself and an automated deduction system for it by (i) providing a formal semantics; (ii) defining a sound resolution-style calculus by refutation; and (iii) describing a first-order proof procedure for PLFC clauses based on (ii) and on a novel notion of most general substitution of two literals in a resolution step. In contrast to standard Possibilistic logic semantics, truth-evaluation of formulas with fuzzy constants are many-valued instead of boolean, and consequently an extended notion of possibilistic uncertainty is also needed.