Motivating explanations in Bayesian networks using MAP-independence

DOI10.1016/j.ijar.2022.11.012OpenAlexW4310069729MaRDI QIDQ2677844

Johan Kwisthout

Publication date: 6 January 2023

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

Full work available at URL: https://arxiv.org/abs/2208.03121

zbMATH Keywords

relevancecomputational complexityBayesian networksexplainable AImost probable explanations

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (1)

Efficient search for relevance explanations using MAP-independence in Bayesian networks

Cites Work

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• On Stopping Evidence Gathering for Diagnostic Bayesian Networks
• Relevance of Evidence in Bayesian Networks
• Modeling and Reasoning with Bayesian Networks
• Most Inforbable Explanations: Finding Explanations in Bayesian Networks That Are Both Probable and Informative

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