1 research outputs found
A DPLL Procedure with Dichotomous Branching for Propositional Product Logic
The propositional product logic is one of the basic fuzzy logics with
continuous t-norms, exploiting the multiplication t-norm on the unit interval
[0,1]. Our aim is to combine well-established automated deduction (theorem
proving) with fuzzy inference. As a first step, we devise a modification of the
procedure of Davis, Putnam, Logemann, and Loveland (DPLL) with dichotomous
branching inferring in the product logic. We prove that the procedure is
refutation sound and finitely complete. As a consequence, solutions to the
deduction, satisfiability, and validity problems will be proposed for the
finite case. The presented results are applicable to a design of intelligent
systems, exploiting some kind of multi-step fuzzy inference