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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Compiling Min-based Possibilistic Causal Networks: A Mutilated-Based Approach
verfasst von : Raouia Ayachi, Nahla Ben Amor, Salem Benferhat
Erschienen in: Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Verlag: Springer Berlin Heidelberg
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Qualitative causal possibilistic networks are important tools for handling uncertain information in the possibility theory framework. Despite their importance, no compilation has been performed to ensure causal reasoning in possibility theory framework. This paper proposes two compilation-based inference algorithms for min-based possibilistic causal networks. The first is a possibilistic adaptation of the probabilistic inference method [8] and the second is a purely possibilistic approach. Both of them are based on an encoding of the network into a propositional theory and a compilation of this output in order to efficiently compute the effect of both observations and interventions, while adopting a mutilation strategy.