Abstract argumentation systems
Artificial Intelligence
Inferring from Inconsistency in Preference-Based Argumentation Frameworks
Journal of Automated Reasoning
Argumentation based decision making for autonomous agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Preference-based argumentation: Arguments supporting multiple values
International Journal of Approximate Reasoning
Using arguments for making and explaining decisions
Artificial Intelligence
Comparing sets of positive and negative arguments: Empirical assessment of seven qualitative rules
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
On the qualitative comparison of decisions having positive and negative features
Journal of Artificial Intelligence Research
Practical reasoning using values: giving meaning to values
ArgMAS'09 Proceedings of the 6th international conference on Argumentation in Multi-Agent Systems
Argumentation based dynamic multiple criteria decision making
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Hi-index | 0.00 |
Preferences between different alternatives (products, decisions, agreements etc.) are often based on multiple criteria. Qualitative Preference Systems (QPS) is a formal framework for the representation of qualitative multi-criteria preferences in which a criterion's preference is defined based on the values of attributes or by combining multiple subcriteria in a cardinality-based or lexicographic way. In this paper we present a language and reasoning mechanism to represent and reason about such qualitative multi-criteria preferences. We take an argumentation-based approach and show that the presented argumentation framework correctly models a QPS. Then we extend this argumentation framework in such a way that it can derive missing information from background knowledge, which makes it more flexible in case of incomplete specifications.