NDLI: Argumentation frameworks as constraint satisfaction problems

Content Provider	Springer Nature Link
Author	Devred, Caroline Amgoud, Leila
Copyright Year	2013
Abstract	Argumentation is a promising approach for defeasible reasoning. It consists of justifying each plausible conclusion by arguments. Since the available information may be inconsistent, a conclusion and its negation may both be justified. The arguments are thus said to be conflicting. The main issue is how to evaluate the arguments. Several semantics were proposed for that purpose. The most important ones are: stable, preferred, complete, grounded and admissible. A semantics is a set of criteria that should be satisfied by a set of arguments, called extension, in order to be acceptable. Different decision problems related to these semantics were defined (like whether an argumentation framework has a stable extension). It was also shown that most of these problems are intractable. Consequently, developing algorithms for these problems is not trivial and thus the implementation of argumentation systems not obvious. Recently, some solutions to this problem were found. The idea is to use a reduction method where a given problem is translated in another one like SAT or ASP. This paper follows this line of research. It studies how to encode the problem of computing the extensions of an argumentation framework (under each of the previous semantics) as a constraint satisfaction problem (CSP). Such encoding is of great importance since it makes it possible to use the very efficient solvers (developed by the CSP community) for computing the extensions. Our encodings take advantage of existing reductions to SAT problems in the case of Dung’s abstract framework. Among the various ways of translating a SAT problem into a CSP one, we propose the most appropriate one in the argumentation context. We also provide encodings in case two other families of argumentation frameworks: the constrained version of Dung’s abstract framework and preference-based argumentation framework.
Ending Page	148
Page Count	18
Starting Page	131
File Format	PDF
ISSN	10122443
e-ISSN	15737470
Journal	Annals of Mathematics and Artificial Intelligence
Issue Number	1
Volume Number	69
Language	English
Publisher	Springer International Publishing
Publisher Date	2013-03-22
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Non-monotonic Reasoning CSP Argumentation Problem solving (heuristics, search strategies, etc.) Computer Science Artificial Intelligence (incl. Robotics) Mathematics Statistical Physics, Dynamical Systems and Complexity Artificial intelligence
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Learning cluster-based structure to solve constraint satisfaction problems

Weight constraint programs with evaluable functions

Heuristics as Markov chains

Static and dynamic structural symmetry breaking

Enhancing numerical constraint propagation using multiple inclusion representations

Set-structured and cost-sharing heuristics for classical planning

On the investigation of hyper-heuristics on a financial forecasting problem

Solving job shop scheduling with setup times through constraint-based iterative sampling: an experimental analysis

Improving local-search metaheuristics through look-ahead policies

Argumentation frameworks as constraint satisfaction problems

Similar Documents

Learning cluster-based structure to solve constraint satisfaction problems

Weight constraint programs with evaluable functions

Heuristics as Markov chains

Static and dynamic structural symmetry breaking

Enhancing numerical constraint propagation using multiple inclusion representations

Set-structured and cost-sharing heuristics for classical planning

On the investigation of hyper-heuristics on a financial forecasting problem

Solving job shop scheduling with setup times through constraint-based iterative sampling: an experimental analysis

Improving local-search metaheuristics through look-ahead policies

Argumentation frameworks as constraint satisfaction problems