Fudge: A light-weight solver for abstract argumentation based on SAT reductions
This work addresses computational challenges in abstract argumentation for AI and logic communities, but it is incremental as it builds on standard translation approaches with specific novel encodings.
The authors tackled the problem of solving abstract argumentation problems by introducing Fudge, a solver that integrates SAT technology and uses novel encodings for skeptical reasoning under preferred and ideal semantics, achieving efficient performance as a light-weight solution.
We present Fudge, an abstract argumentation solver that tightly integrates satisfiability solving technology to solve a series of abstract argumentation problems. While most of the encodings used by Fudge derive from standard translation approaches, Fudge makes use of completely novel encodings to solve the skeptical reasoning problem wrt. preferred semantics and problems wrt. ideal semantics.