Controllability of Control Argumentation Frameworks

Andreas Niskanen, Daniel Neugebauer, Matti Järvisalo

IJCAI 2020 pp. 1855-1861

doi:10.24963/IJCAI.2020/257 /ijcai/2020/niskanen2020ijcai-controllability/

Abstract

Control argumentation frameworks (CAFs) allow for modeling uncertainties inherent in various argumentative settings. We establish a complete computational complexity map of the central computational problem of controllability in CAFs for five key semantics. We also develop Boolean satisfiability based counterexample-guided abstraction refinement algorithms and direct encodings of controllability as quantified Boolean formulas, and empirically evaluate their scalability on a range of NP-hard variants of controllability.

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Text

Niskanen et al. "Controllability of Control Argumentation Frameworks." International Joint Conference on Artificial Intelligence, 2020. doi:10.24963/IJCAI.2020/257

Markdown

[Niskanen et al. "Controllability of Control Argumentation Frameworks." International Joint Conference on Artificial Intelligence, 2020.](https://mlanthology.org/ijcai/2020/niskanen2020ijcai-controllability/) doi:10.24963/IJCAI.2020/257

BibTeX

@inproceedings{niskanen2020ijcai-controllability,
  title     = {{Controllability of Control Argumentation Frameworks}},
  author    = {Niskanen, Andreas and Neugebauer, Daniel and Järvisalo, Matti},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {1855-1861},
  doi       = {10.24963/IJCAI.2020/257},
  url       = {https://mlanthology.org/ijcai/2020/niskanen2020ijcai-controllability/}
}