Belief structures, possibility theory and decomposable confidence measures on finite sets
Computers and Artificial Intelligence
An axiomatic treatment of three qualitative decision criteria
Journal of the ACM (JACM)
Towards a Possibilistic Logic Handling of Preferences
Applied Intelligence
Using arguments for making decisions: a possibilistic logic approach
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
A unified framework for order-of-magnitude confidence relations
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Qualitative decision under uncertainty: back to expected utility
Artificial Intelligence
Elements of Argumentation
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
Explaining qualitative decision under uncertainty by argumentation
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Defining relative likelihood in partially-ordered preferential structures
Journal of Artificial Intelligence Research
Generalized qualitative probability: savage revisited
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
An argumentation-based approach to multiple criteria decision
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
On the qualitative comparison of sets of positive and negative affects
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
The balancing Choquet integral
Fuzzy Sets and Systems
Dealing with the dynamics of proof-standard in argumentation-based decision aiding
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Preferences in AI: An overview
Artificial Intelligence
Bipolar aggregation using the Uninorms
Fuzzy Optimization and Decision Making
An argumentation framework for deriving qualitative risk sensitive preferences
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Gradualness, uncertainty and bipolarity: Making sense of fuzzy sets
Fuzzy Sets and Systems
An argumentation framework for qualitative multi-criteria preferences
TAFA'11 Proceedings of the First international conference on Theory and Applications of Formal Argumentation
The role of fuzzy sets in decision sciences: Old techniques and new directions
Fuzzy Sets and Systems
Mathematical morphology on bipolar fuzzy sets: general algebraic framework
International Journal of Approximate Reasoning
Qualitative integrals and desintegrals --- towards a logical view
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
A fuzzy and bipolar approach to preference modeling with application to need and desire
Fuzzy Sets and Systems
Preferences with qualitative thresholds and methods for individual and collective decisions
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Deliberation about preferences and group decisions
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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Making a decision is often a matter of listing and comparing positive and negative arguments. In such cases, the evaluation scale for decisions should be considered bipolar, that is, negative and positive values should be explicitly distinguished. That is what is done, for example, in Cumulative Prospect Theory. However, contrary to the latter framework that presupposes genuine numerical assessments, human agents often decide on the basis of an ordinal ranking of the pros and the cons, and by focusing on the most salient arguments. In other terms, the decision process is qualitative as well as bipolar. In this article, based on a bipolar extension of possibility theory, we define and axiomatically characterize several decision rules tailored for the joint handling of positive and negative arguments in an ordinal setting. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case, and consequently suffer from poor decisive power. More decisive rules that refine the former are also proposed. These refinements agree both with principles of efficiency and with the spirit of order-of-magnitude reasoning, that prevails in qualitative decision theory. The most refined decision rule uses leximin rankings of the pros and the cons, and the ideas of counting arguments of equal strength and cancelling pros by cons. It is shown to come down to a special case of Cumulative Prospect Theory, and to subsume the "Take the Best" heuristic studied by cognitive psychologists.