Abduction with Penalization in Logic Programming

TL;DR

This paper introduces a novel form of abductive reasoning with penalization in logic programming, demonstrating its expressiveness and complexity, and applying it to problems like the Traveling Salesman Problem.

Contribution

It formalizes abduction with penalization in logic programming, extending existing frameworks, and shows its high expressiveness and complexity, including encoding complex optimization problems.

Findings

Encoding of Traveling Salesman Problem in the framework

Negation does not increase reasoning complexity

Formal model extends previous abductive frameworks

Abstract

Abduction, first proposed in the setting of classical logics, has been studied with growing interest in the logic programming area during the last years. In this paper we study {\em abduction with penalization} in logic programming. This form of abductive reasoning, which has not been previously analyzed in logic programming, turns out to represent several relevant problems, including optimization problems, very naturally. We define a formal model for abduction with penalization from logic programs, which extends the abductive framework proposed by Kakas and Mancarella. We show the high expressiveness of this formalism, by encoding a couple of relevant problems, including the well-know Traveling Salesman Problem from optimization theory, in this abductive framework. The resulting encodings are very simple and elegant. We analyze the complexity of the main decisional problems arising in this framework. An interesting result in this course is that ``negation comes for free.'' Indeed, the addition of (even unstratified) negation does not cause any further increase to the complexity of the abductive reasoning tasks (which remains the same as for not-free programs).