Author:
Ivor Uhliarik
Affiliation:
Comenius University, Slovak Republic
Keyword(s):
Fuzzy ASP, Fuzzy Logic, Answer Set Programming, Product Logic, Stable Models, DPLL.
Related
Ontology
Subjects/Areas/Topics:
Approximate Reasoning and Fuzzy Inference
;
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Systems
;
Soft Computing
Abstract:
In recent years, foundations have been laid for a turn in logic programming paradigms in continuous domains. Fuzzy answer set programming (FASP) has emerged as a combination of a tool for non-monotonic reasoning and solving combinatorial problems (ASP) and a knowledge representation formalism that allows for modeling partial truth (fuzzy logic). There have been various attempts at designing a solver for FASP, but they either make use of transformations into optimization programs with scaling problems, operate only on finite-valued Łukasiewicz logic, or yield only approximate answer sets. Moreover, there has been no research focused on the product logic semantics in FASP. In this work we investigate the methods used in state-of-the-art classical ASP solvers with the aim of designing a FASP solver for product propositional logic. In particular, we base our approach on the conversion into fuzzy SAT (satisfiability problem) and the fuzzy generalization of the DPLL algorithm. Since both Ł
ukasiewicz and (extended) Gödel logic can be embedded into product logic, the resulting system should be able to operate on all three logics uniformly.
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