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Answer set programming (ASP) is a popular nonmonotonic-logic based paradigmfor knowledge representation and solving combinatorial problems. Computing theanswer set of an ASP program is NP-hard in general, and researchers have beeninvesting significant effort to speed it up. The majority of current ASPsolvers employ SAT solver-like technology to find these answer sets. As aresult, justification for why a literal is in the answer set is hard toproduce. There are dependency graph based approaches to find answer sets, butdue to the representational limitations of dependency graphs, such approachesare limited. We propose a novel dependency graph-based approach for findinganswer sets in which conjunction of goals is explicitly represented as a nodewhich allows arbitrary answer set programs to be uniformly represented. Ourrepresentation preserves causal relationships allowing for justification foreach literal in the answer set to be elegantly found. Performance results froman implementation are also reported. Our work paves the way for computinganswer sets without grounding a program.

grASP: A Graph Based ASP-Solver and Justification System