On the transformation between possibilistic logic bases and possibilistic causal networks

DOI10.1016/S0888-613X(01)00061-5zbMath1015.68204arXiv1301.6679OpenAlexW2073713926MaRDI QIDQ1347872

Henri Prade, Salem Benferhat, Laurent Garcia, Dubois, Didier

Publication date: 15 May 2002

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

Full work available at URL: https://arxiv.org/abs/1301.6679

zbMATH Keywords

possibilistic logicmin-based graphpossibilistic graphspossibilistic knowledge base

Mathematics Subject Classification ID

Knowledge representation (68T30) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (24)

DAG representation of asymmetric independence models arising in coherent conditional possibility theory ⋮ Possibilistic Conditional Preference Networks ⋮ Complexity results and algorithms for possibilistic influence diagrams ⋮ Possibilistic logic: a retrospective and prospective view ⋮ LEG Networks for Ranking Functions ⋮ Hybrid possibilistic networks ⋮ Quantitative possibility theory: logical- and graphical-based representations ⋮ Characterizing and extending answer set semantics using possibility theory ⋮ Using inductive reasoning for completing OCF-networks ⋮ Possibilistic preference networks ⋮ Efficient processing of twig query with compound predicates in fuzzy XML ⋮ Modeling positive and negative information in possibility theory ⋮ CP-Nets, $$\pi $$-pref Nets, and Pareto Dominance ⋮ PRODUCT-BASED CAUSAL NETWORKS AND QUANTITATIVE POSSIBILISTIC BASES ⋮ Compiling Min-based Possibilistic Causal Networks: A Mutilated-Based Approach ⋮ Uncertain logical gates in possibilistic networks: theory and application to human geography ⋮ PRODUCT-BASED CAUSAL NETWORKS AND QUANTITATIVE POSSIBILISTIC BASES ⋮ Possibilistic networks for information retrieval ⋮ Algorithms for possibility assessments: coherence and extension ⋮ Inferring interventions in product-based possibilistic causal networks ⋮ Predicting causality ascriptions from background knowledge: model and experimental validation ⋮ Inference using compiled min-based possibilistic causal networks in the presence of interventions ⋮ Editorial: Fuzzy set and possibility theory-based methods in artificial intelligence ⋮ Fuzzy \(rr\)DFCSP and planning

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