Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Handbook of logic in artificial intelligence and logic programming (vol. 3)
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Abduction from logic program: semantics and complexity
Theoretical Computer Science
Extending and implementing the stable model semantics
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Enhancing Disjunctive Datalog by Constraints
IEEE Transactions on Knowledge and Data Engineering
Abduction in Logic Programming
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
Smodels - An Implementation of the Stable Model and Well-Founded Semantics for Normal LP
LPNMR '97 Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning
Artificial Intelligence - Special issue on nonmonotonic reasoning
System Z: a natural ordering of defaults with tractable applications to nonmonotonic reasoning
TARK '90 Proceedings of the 3rd conference on Theoretical aspects of reasoning about knowledge
Abductive logic programs with penalization: semantics, complexity and implementation
Theory and Practice of Logic Programming
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Possibilistic uncertainty handling for answer set programming
Annals of Mathematics and Artificial Intelligence
The Diagnosis Frontend of the dlv system
AI Communications
Argumentation-Based Inference and Decision Making--A Medical Perspective
IEEE Intelligent Systems
Using arguments for making and explaining decisions
Artificial Intelligence
Dealing Automatically with Exceptions by Introducing Specificity in ASP
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Conflict-driven answer set solving
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Possibility theory as a basis for qualitative decision theory
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
On the foundations of qualitative decision theory
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Argumentation and answer set programming
Logic programming, knowledge representation, and nonmonotonic reasoning
ASPIDE: integrated development environment for answer set programming
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Answer set programming for computing decisions under uncertainty
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Handling exceptions in logic programming without negation as failure
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Arguing for decisions: a qualitative model of decision making
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
A Possibilistic Argumentation Decision Making Framework with Default Reasoning
Fundamenta Informaticae - Latin American Workshop on Logic Languages, Algorithms and New Methods of Reasoning (LANMR)
Using Possibilistic Logic for Modeling Qualitative Decision: ATMS-based Algorithms
Fundamenta Informaticae
Dealing with explicit preferences and uncertainty in answer set programming
Annals of Mathematics and Artificial Intelligence
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A qualitative approach to decision making under uncertainty has been proposed in the setting of possibility theory, which is based on the assumption that levels of certainty and levels of priority (for expressing preferences) are commensurate. In this setting, pessimistic and optimistic decision criteria have been formally justified. This approach has been transposed into possibilistic logic in which the available knowledge is described by formulas which are more or less certainly true and the goals are described in a separate prioritized base. This paper adapts the possibilistic logic handling of qualitative decision making under uncertainty in the Answer Set Programming (ASP) setting. We show how weighted beliefs and prioritized preferences belonging to two separate knowledge bases can be handled in ASP by modeling qualitative decision making in terms of abductive logic programming where (uncertain) knowledge about the world and prioritized preferences are encoded as possibilistic definite logic programs and possibilistic literals respectively. We provide ASP-based and possibilistic ASP-based algorithms for calculating optimal decisions and utility values according to the possibilistic decision criteria. We describe a prototype implementing the algorithms proposed on top of different ASP solvers and we discuss the complexity of the different implementations.