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Undercutting in argumentation systems
- Source :
- SUM 2015: Scalable Uncertainty Management, International Conference on Scalable Uncertainty Management (SUM 2015), International Conference on Scalable Uncertainty Management (SUM 2015), Sep 2015, Quebec, Canada. pp. 267-281, Lecture Notes in Computer Science ISBN: 9783319235394, SUM
- Publication Year :
- 2015
- Publisher :
- HAL CCSD, 2015.
-
Abstract
- International audience; Rule-based argumentation systems are developed for reasoning about defeasible information. They take as input a theory made of a set of strict rules, which encode strict information, and a set of defeasible rules which describe general behaviour with exceptional cases. They build arguments by chaining such rules, define attacks between them, use a semantics for evaluating the arguments, and finally identify the plausible conclusions that follow from the rules. One of the main attack relations of such systems is the so-called undercutting which blocks the application of defeasible rules in some contexts. In this paper, we show that this relation is powerful enough to capture alone all the different conflicts in a theory. We present the first argumentation system that uses only undercutting and fully characterize both its extensions and its plausible conclusions under various acceptability semantics.
- Subjects :
- Logique en informatique
Acceptability semantics
Theoretical computer science
Relation (database)
Semantics (computer science)
business.industry
Rule-based argumentation
[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]
Defeasible estate
Informatique et langage
Intelligence artificielle
16. Peace & justice
ENCODE
Apprentissage
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Argumentation theory
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Set (abstract data type)
Undercutting
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
Chaining
Artificial intelligence
business
Mathematics
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-319-23539-4
- ISBNs :
- 9783319235394
- Database :
- OpenAIRE
- Journal :
- SUM 2015: Scalable Uncertainty Management, International Conference on Scalable Uncertainty Management (SUM 2015), International Conference on Scalable Uncertainty Management (SUM 2015), Sep 2015, Quebec, Canada. pp. 267-281, Lecture Notes in Computer Science ISBN: 9783319235394, SUM
- Accession number :
- edsair.doi.dedup.....333f13e37712e03249cfdb726f53f8c3