2013/03/27 by Michael P. Wellman, Wellman, Michael P.
Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Biomedical Text Mining and Ontologies #Cognitive Science and Mapping #FOS: Computer and information sciences #Semantic Web and Ontologies #cs.AI
paper · pdf · doi:10.48550/arxiv.1304.1081
Appears in Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence (UAI1990)
arxiv created 2013/03/27 · openalex publication_date 2013/03/27 · arxiv updated 2013/04/05 · openalex created_date 2022/08/30 · openalex updated_date 2026/07/28
Functional dependencies restrict the potential interactions among variables connected in a probabilistic network. This restriction can be exploited in qualitative probabilistic reasoning by introducing deterministic variables and modifying the inference rules to produce stronger conclusions in the presence of functional relations. I describe how to accomplish these modifications in qualitative probabilistic networks by exhibiting the update procedures for graphical transformations involving probabilistic and deterministic variables and combinations. A simple example demonstrates that the augmented scheme can reduce qualitative ambiguity that would arise without the special treatment of functional dependency. Analysis of qualitative synergy reveals that new higher-order relations are required to reason effectively about synergistic interactions among deterministic variables.