Explaining Bayesian Networks Using Argumentation

DOI10.1007/978-3-319-20807-7_8zbMath1465.68243OpenAlexW1028871446MaRDI QIDQ3451167

Sjoerd T. Timmer, Bart Verheij, Silja Renooij, Henry Prakken, John-Jules Ch. Meyer

Publication date: 10 November 2015

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-20807-7_8

zbMATH Keywords

uncertaintyBayesian networksreasoningexplanationinferenceargumentation

Mathematics Subject Classification ID

Logic in artificial intelligence (68T27) Reasoning under uncertainty in the context of artificial intelligence (68T37) Probabilistic graphical models (62H22)

Related Items (7)

A two-phase method for extracting explanatory arguments from Bayesian networks ⋮ Persuasive contrastive explanations for Bayesian networks ⋮ A Bayesian approach to forward and inverse abstract argumentation problems ⋮ Forecasting with jury-based probabilistic argumentation ⋮ Descriptive accuracy in explanations: the case of probabilistic classifiers ⋮ Efficient search for relevance explanations using MAP-independence in Bayesian networks ⋮ A labelling framework for probabilistic argumentation

Cites Work

• A general account of argumentation with preferences
• A mathematical treatment of defeasible reasoning and its implementation.
• Justification and defeat
• Abstract argumentation systems
• On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and \(n\)-person games
• Bayesian Networks and Probabilistic Inference in Forensic Science
• Unnamed Item

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