An Extension-Based Approach to Belief Revision in Abstract Argumentation
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Special Track on Knowledge Representation and Reasoning. Pages 2926-2931.
Abstract
Argumentation is an inherently dynamic process. Consequently, recent years have witnessed tremendous research efforts towards an understanding of how the seminal AGM theory of belief change can be applied to argumentation, in particular for Dung's abstract argumentation frameworks (AFs). However, none of the attempts has yet succeeded in handling the natural situation where the revision of an AF is guaranteed to be representable by an AF as well. In this work, we present a generic solution to this problem which applies to many prominent I-maximal argumentation semantics. In order to prove a full representation theorem, we make use of recent advances in both areas of argumentation and belief change. In particular, we utilize the concepts of realizability in argumentation and the notion of compliance as used in Horn revision.
@inproceedings{ijcai2015p414,
title = {An Extension-Based Approach to Belief Revision in Abstract Argumentation},
author = {Diller, Martin and Haret, Adrian and Linsbichler, Thomas and Rümmele, Stefan and Woltran, Stefan},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {2926--2931},
year = {2015},
month = {7},
note = {Special Track on Knowledge Representation and Reasoning},
url = {https://ijcai.org/proceedings/2015/414},
}
TY - CPAPER TI - An Extension-Based Approach to Belief Revision in Abstract Argumentation AU - Diller, Martin AU - Haret, Adrian AU - Linsbichler, Thomas AU - Rümmele, Stefan AU - Woltran, Stefan T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 2926 EP - 2931 UR - https://ijcai.org/proceedings/2015/414 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: