An answer set is a plain set of literals which has no further structure that would explain why certain literals are part of it and why others are not. We show how argumentation theory can help to explain why a literal is or is not contained in a given answer set by defining two justification methods, both of which make use of the correspondence between answer sets of a logic program and stable extensions of the assumption-based argumentation (ABA) framework constructed from the same logic program. Attack Trees justify a literal in argumentation-theoretic terms, i.e. using arguments and attacks between them, whereas ABA-Based Answer Set Justifications express the same justification structure in logic programming terms, that is using literals and their relationships. Interestingly, an ABA-Based Answer Set Justification corresponds to an admissible fragment of the answer set in question, and an Attack Tree corresponds to an admissible fragment of the stable extension corresponding to this answer set.
@cite_18: This paper describes the problems with debugging tools for answer set programming, a declarative programming paradigm. Current approaches are difficult to use on most applications due to the considerable bottlenecks in communicating the reasons to the user. In this paper we examine the reasons for this and suggest some possible future directions.
@cite_10: The paper introduces the notion of offline justification for answer set programming (ASP). Justifications provide a graph-based explanation of the truth value of an atom with respect to a given answer set. The paper extends also this notion to provide justification of atoms during the computation of an answer set (on-line justification) and presents an integration of online justifications within the computation model of SMODELS. Offline and online justifications provide useful tools to enhance understanding of ASP, and they offer a basic data structure to support methodologies and tools for debugging answer set programs. A preliminary implementation has been developed in .
So far, the problem of justifying answer sets has not received much attention, even though the need for justifications has been expressed @cite_18 . According to @cite_10 , a justification should provide only the information that are relevant to the item being explained'', making it easier understandable. We incorporate this in ABAS Justifications by not using the whole derivation of a literal, but only the underlying facts and NAF literals necessary to derive the literal in question.