Name
Abstract | ||
|---|---|---|
In the context of abstract argumentation frameworks, the admissibility problem is about deciding whether a given argument (i.e. piece of knowledge) is admissible in a conflicting knowledge base. In this paper we present an enhanced backtracking-based algorithm for solving the admissibility problem. The algorithm performs successfully when applied to a wide range of benchmark abstract argumentation frameworks and when compared to the state-of-the-art algorithm. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.5220/0008064300670075 | KEOD: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL 2: KEOD |
Keywords | Field | DocType |
Argument-based Knowledge Base, Argument-based Reasoning, Computational Argumentation, Algorithms | Data mining,Computer science,Argumentation theory,Theoretical computer science,Knowledge base,Backtracking | Conference |
Volume | Citations | PageRank |
2 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samer Nofal | 1 | 0 | 0.34 |
| Katie Atkinson | 2 | 849 | 77.06 |
| Paul E. Dunne | 3 | 1700 | 112.42 |