Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

On the Complexity of Probabilistic Abstract Argumentation Frameworks

On the Complexity of Probabilistic Abstract Argumentation Frameworks Probabilistic abstract argumentation combines Dungs abstract argumentation framework with probability theory in order to model uncertainty in argumentation. In this setting, we address the fundamental problem of computing the probability that a set of arguments is an extension according to a given semantics. We focus on the most popular semantics (i.e., admissible, stable, complete, grounded, preferred, ideal-set, ideal, stage, and semistable) and show the following dichotomy result: computing the probability that a set of arguments is an extension is either FP or FPP-complete depending on the semantics adopted. Our polynomial-time results are particularly interesting, as they hold for some semantics for which no polynomial-time technique was known so far. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computational Logic (TOCL) Association for Computing Machinery

On the Complexity of Probabilistic Abstract Argumentation Frameworks

Loading next page...
 
/lp/association-for-computing-machinery/on-the-complexity-of-probabilistic-abstract-argumentation-frameworks-h0pWP1poCo

References (74)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 ACM
ISSN
1529-3785
eISSN
1557-945X
DOI
10.1145/2749463
Publisher site
See Article on Publisher Site

Abstract

Probabilistic abstract argumentation combines Dungs abstract argumentation framework with probability theory in order to model uncertainty in argumentation. In this setting, we address the fundamental problem of computing the probability that a set of arguments is an extension according to a given semantics. We focus on the most popular semantics (i.e., admissible, stable, complete, grounded, preferred, ideal-set, ideal, stage, and semistable) and show the following dichotomy result: computing the probability that a set of arguments is an extension is either FP or FPP-complete depending on the semantics adopted. Our polynomial-time results are particularly interesting, as they hold for some semantics for which no polynomial-time technique was known so far.

Journal

ACM Transactions on Computational Logic (TOCL)Association for Computing Machinery

Published: Jun 2, 2015

Keywords: Computational complexity

There are no references for this article.