Handbook of logic in artificial intelligence and logic programming (vol. 3)
ACM Computing Surveys (CSUR)
A logic-based theory of deductive arguments
Artificial Intelligence
A Complete Calcultis for Possibilistic Logic Programming with Fuzzy Propositional Variables
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
A logic programming framework for possibilistic argumentation with vague knowledge
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Towards higher impact argumentation
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Argument-based critics and recommenders: a qualitative perspective on user support systems
Data & Knowledge Engineering - Special issue: WIDM 2004
International Journal of Approximate Reasoning
Recommender System Technologies based on Argumentation 1
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
A lattice-based approach to computing warranted beliefs in skeptical argumentation frameworks
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A characterization of collective conflict for defeasible argumentation
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
Concept convergence in empirical domains
DS'10 Proceedings of the 13th international conference on Discovery science
A computational method for defeasible argumentation based on a recursive warrant semantics
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Maximal ideal recursive semantics for defeasible argumentation
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
A heuristics-based pruning technique for argumentation trees
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Argumentation-Supported information distribution in a multiagent system for knowledge management
ArgMAS'05 Proceedings of the Second international conference on Argumentation in Multi-Agent Systems
Empirical argumentation: integrating induction and argumentation in MAS
ArgMAS'10 Proceedings of the 7th international conference on Argumentation in Multi-Agent Systems
Deliberation dialogues for reasoning about safety critical actions
Autonomous Agents and Multi-Agent Systems
Modelling argument accrual with possibilistic uncertainty in a logic programming setting
Information Sciences: an International Journal
Using argument strength for building dialectical bonsai
Annals of Mathematics and Artificial Intelligence
| Hi-index | 0.00 |
Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at object-language level. Solving a P-DeLP query Q accounts for performing an exhaustive analysis of arguments and defeaters for Q, resulting in a so-called dialectical tree, usually computed in a depth-first fashion. Computing dialectical trees efficiently in P-DeLP is an important issue, as some dialectical trees may be computationally more expensive than others which lead to equivalent results. In this paper we explore different aspects concerning how to speed up dialectical inference in P-DeLP. We introduce definitions which allow to characterize dialectical trees constructively rather than declaratively, identifying relevant features for pruning the associated search space. The resulting approach can be easily generalized to be applied in other argumentation frameworks based in logic programming.