On the complexity of belief network synthesis and refinement

DOI10.1016/0888-613X(92)90007-MzbMath0769.68114OpenAlexW2094281172MaRDI QIDQ1207964

Marco Valtorta, Donald W. Loveland

Publication date: 16 May 1993

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0888-613x(92)90007-m

zbMATH Keywords

synthesisBayesian networksNP-completenessexpert systemsknowledge acquisitionDempster-Shafer theory of evidenceknowledge base refinementbelief netsDempster- Shafer networks

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (1)

Knowledge base refinement: A bibliography

Cites Work

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• Adapting connectionist learning to Bayes networks
• A logic-based analysis of Dempster-Shafer theory
• Bayesian and non-Bayesian evidential updating
• Propagating belief functions in qualitative Markov trees
• Belief functions and default reasoning
• Dempster's rule of combination is {\#}P-complete
• The computational complexity of probabilistic inference using Bayesian belief networks
• A method for managing evidential reasoning in a hierarchical hypothesis space: a retrospective

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