General patterns in nonmonotonic reasoning
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Foundations of logic programming
Principles of knowledge representation
ACM Computing Surveys (CSUR)
The Possibilistic Handling of Irrelevance in Exception-Tolerant Reasoning
Annals of Mathematics and Artificial Intelligence
Inferring from Inconsistency in Preference-Based Argumentation Frameworks
Journal of Automated Reasoning
A Proof Procedure for Possibilistic Logic Programming with Fuzzy Constants
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A logic programming framework for possibilistic argumentation with vague knowledge
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
A complete calculus for possibilistic logic programming with fuzzy propositional variables
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Argumentative inference in uncertain and inconsistent knowledge bases
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
Argument-based critics and recommenders: a qualitative perspective on user support systems
Data & Knowledge Engineering - Special issue: WIDM 2004
On Warranted Inference in Possibilistic Defeasible Logic Programming
Proceedings of the 2005 conference on Artificial Intelligence Research and Development
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
Computing dialectical trees efficiently in possibilistic defeasible logic programming
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
ONTOarg: A decision support framework for ontology integration based on argumentation
Expert Systems with Applications: An International Journal
| 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. Defeasible argumentation in general and P-DeLP in particular provide a way of modelling non-monotonic inference. From a logical viewpoint, capturing defeasible inference relationships for modelling argument and warrant is particularly important, as well as the study of their logical properties. This paper analyzes two non-monotonic operators for P-DeLP which model the expansion of a given program $\mathcal{P}$ by adding new weighed facts associated with argument conclusions and warranted literals, resp. Different logical properties for the proposed expansion operators are studied and contrasted with a traditional SLD-based Horn logic. We will show that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworks.