Exploiting Parallelism for Hard Problems in Abstract Argumentation

Abstract

Abstract argumentation framework (AF) 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 AFs are missing, thus 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.

Cite

Text

Cerutti et al. "Exploiting Parallelism for Hard Problems in Abstract Argumentation." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9395

Markdown

[Cerutti et al. "Exploiting Parallelism for Hard Problems in Abstract Argumentation." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/cerutti2015aaai-exploiting/) doi:10.1609/AAAI.V29I1.9395

BibTeX

@inproceedings{cerutti2015aaai-exploiting,
  title     = {{Exploiting Parallelism for Hard Problems in Abstract Argumentation}},
  author    = {Cerutti, Federico and Tachmazidis, Ilias and Vallati, Mauro and Batsakis, Sotirios and Giacomin, Massimiliano and Antoniou, Grigoris},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {1475-1481},
  doi       = {10.1609/AAAI.V29I1.9395},
  url       = {https://mlanthology.org/aaai/2015/cerutti2015aaai-exploiting/}
}