Exploiting Parallelism for Hard Problems in Abstract Argumentation: Technical Report
This work addresses a bottleneck in applying argumentation-based reasoning to real domains by improving computational efficiency, though it is incremental as it builds on existing semantics.
The paper tackles the problem of efficiently enumerating preferred extensions in abstract argumentation frameworks by developing a parallel algorithm based on SCC-recursive semantics, resulting in significant performance improvements in large frameworks with increased solution counts and speedup.
Abstract argumentation framework (\AFname) is a unifying framework able to encompass a variety of nonmonotonic reasoning approaches, logic programming and computational argumentation. Yet, efficient approaches for most of the decision and enumeration problems associated to \AFname s are missing, thus potentially limiting the efficacy of argumentation-based approaches in real domains. In this paper, we present an algorithm for enumerating the preferred extensions of abstract argumentation frameworks which exploits parallel computation. To this purpose, the SCC-recursive semantics definition schema is adopted, where extensions are defined at the level of specific sub-frameworks. The algorithm shows significant performance improvements in large frameworks, in terms of number of solutions found and speedup.