On the specificity of a possibility distribution
Fuzzy Sets and Systems
Possibilistic constraint satisfaction problems or “how to handle soft constraints?”
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Refinements of the maximin approach to decision-making in a fuzzy environment
Fuzzy Sets and Systems - Special issue on fuzzy optimization
Nonmonotonic reasoning, conditional objects and possibility theory
Artificial Intelligence
Logical representation and computation of optimal decisions in a qualitative setting
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Fuzzy sets as a basis for a theory of possibility
Fuzzy Sets and Systems
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Parameters for Utilitarian Desires in a Qualitative Decision Theory
Applied Intelligence
IEEE Transactions on Knowledge and Data Engineering
FAIR '91 Proceedings of the International Workshop on Fundamentals of Artificial Intelligence Research
Towards a Possibilistic Logic Handling of Preferences
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Preferences; Putting More Knowledge into Queries
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Reasoning in Inconsistent Stratified Knowledge Bases
ISMVL '96 Proceedings of the 26th International Symposium on Multiple-Valued Logic
Qualitative relevance and independence: a roadmap
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Reasoning with conditional ceteris paribus preference statements
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Artificial Intelligence - Special issue: Fuzzy set and possibility theory-based methods in artificial intelligence
Modelling uncertain positive and negative reasons in decision aiding
Decision Support Systems
Introducing Grades in Deontic Logics
DEON '08 Proceedings of the 9th international conference on Deontic Logic in Computer Science
Journal of Artificial Intelligence Research
On the qualitative comparison of decisions having positive and negative features
Journal of Artificial Intelligence Research
Ranking alternatives on the basis of generic constraints and examples: a possibilistic approach
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Database preferences queries: a possibilistic logic approach with symbolic priorities
FoIKS'08 Proceedings of the 5th international conference on Foundations of information and knowledge systems
Keeping secrets in possibilistic knowledge bases with necessity-valued privacy policies
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Specifying and computing preferred plans
Artificial Intelligence
Preferences in AI: An overview
Artificial Intelligence
A graded BDI agent model to represent and reason about preferences
Artificial Intelligence
Qualitative model of game theory
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
On the combination of logical and probabilistic models for information analysis
Applied Intelligence
Permissions and uncontrollable propositions in DSDL3: non-monotonicity and algorithms
DEON'06 Proceedings of the 8th international conference on Deontic Logic and Artificial Normative Systems
Database preference queries--a possibilistic logic approach with symbolic priorities
Annals of Mathematics and Artificial Intelligence
Nested Preferences in Answer Set Programming
Fundamenta Informaticae - Latin American Workshop on Logic Languages, Algorithms and New Methods of Reasoning (LANMR)
Dealing with explicit preferences and uncertainty in answer set programming
Annals of Mathematics and Artificial Intelligence
Conditional preference nets and possibilistic logic
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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The classical way of encoding preferences in decision theory is by means of utility or value functions. However agents are not always able to deliver such a function directly. In this paper, we relate three different ways of specifying preferences, namely by means of a set of particular types of constraints on the utility function, by means of an ordered set of prioritized goals expressed by logical propositions, and by means of an ordered set of subsets of possible choices reaching the same level of satisfaction. These different expression modes can be handled in a weighted logical setting, here the one of possibilistic logic. The aggregation of preferences pertaining to different criteria can then be handled by fusing sets of prioritized goals. Apart from a better expressivity, the benefits of a logical representation of preferences are to put them in a suitable format for reasoning purposes, or for modifying them.