Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
Some results concerning the computational complexity of abduction
Proceedings of the first international conference on Principles of knowledge representation and reasoning
The complexity of propositional closed world reasoning and circumscription
Journal of Computer and System Sciences
The complexity of logic-based abduction
Journal of the ACM (JACM)
Semantics and complexity of abduction from default theories
Artificial Intelligence
Consistency restoriation and explanations in dynamic CSPs----application to configuration
Artificial Intelligence
A Complete Classification of the Complexity of Propositional Abduction
SIAM Journal on Computing
What makes propositional abduction tractable
Artificial Intelligence
Bounded treewidth as a key to tractability of knowledge representation and reasoning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Updates, actions, and planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Inference of gene relations from microarray data by abduction
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
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Logic-based abduction is an important reasoning method with many applications in Artificial Intelligence including diagnosis, planning, and configuration. The goal of an abduction problem is to find a “solution”, i.e., an explanation for some observed symptoms. Usually, many solutions exist, and one is often interested in minimal ones only. Previous definitions of “solutions” to an abduction problem tacitly made an open-world assumption. However, as far as minimality is concerned, this assumption may not always lead to the desired behavior. To overcome this problem, we propose a new definition of solutions based on a closed-world approach. Moreover, we also introduce a new variant of minimality where only a part of the hypotheses is subject to minimization. A thorough complexity analysis reveals the close relationship between these two new notions as well as the differences compared with previous notions of solutions.