Published:
2018-02-08
Proceedings:
Proceedings of the AAAI Conference on Artificial Intelligence, 32
Volume
Issue:
Thirty-Second AAAI Conference on Artificial Intelligence 2018
Track:
AAAI Technical Track: Knowledge Representation and Reasoning
Downloads:
Abstract:
Abstract argumentation frameworks are a well-established formalism to model nonmonotonic reasoning processes. However, the standard model cannot express incomplete or conflicting knowledge about the state of a given argumentation. Previously, argumentation frameworks were extended to allow uncertainty regarding the set of attacks or the set of arguments. We combine both models into a model of general incompleteness, complement previous results on the complexity of the verification problem in incomplete argumentation frameworks, and provide a full complexity map covering all three models and all classical semantics. Our main result shows that the complexity of verifying the preferred semantics rises from coNP- to Sigma^p_2-completeness when allowing uncertainty about either attacks or arguments, or both.
DOI:
10.1609/aaai.v32i1.11562
AAAI
Thirty-Second AAAI Conference on Artificial Intelligence 2018
ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)
Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.