An incremental method for generating prime implicants/implicates
Journal of Symbolic Computation
Characterizing diagnoses and systems
Artificial Intelligence
A new method for consequence finding and compilation in restricted languages
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
The Complexity of Restricted Consequence Finding and Abduction
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Global Cut Framework for Removing Symmetries
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Multi-resolution on compressed sets of clauses
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Representative explanations for over-constrained problems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Journal of Artificial Intelligence Research
Knowledge compilation using theory prime implicates
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Possible conflicts: a compilation technique for consistency-based diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In interactive decision-making settings, such as product configuration, users are stating preferences, or foreground constraints, over a set of possible solutions, as defined by background constraints. When the foreground constraints introduce inconsistencies with the background constraints, we wish to find explanations that help the user converge to a solution. In order to provide satisfactory explanations, it can be useful to know one or several subsets of conflicting constraints; such a subset is called a conflict. When computing such conflicts is intractable in an interactive context, we can choose to compile the problem so as to allow faster response times. In this paper we propose a new representation, which implicitly encompasses all conflicts possibly introduced by a user's choices. We claim that it can help in situations where extra information about conflicts is needed, such as when explanations of inconsistency are required.