Relational Probabilistic Conditional Reasoning at Maximum Entropy

DOI10.1007/978-3-642-22152-1_38zbMath1341.68270OpenAlexW2131164511MaRDI QIDQ3011965

Matthias Thimm, Jens Fisseler, Gabriele Kern-Isberner

Publication date: 29 June 2011

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

Full work available at URL: https://doi.org/10.1007/978-3-642-22152-1_38

Mathematics Subject Classification ID

Logic in artificial intelligence (68T27) Knowledge representation (68T30) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items

Quasi conjunction, quasi disjunction, t-norms and t-conorms: probabilistic aspects ⋮ Achieving parametric uniformity for knowledge bases in a relational probabilistic conditional logic with maximum entropy semantics ⋮ Probabilistic argumentation: an approach based on conditional probability. A preliminary report

Cites Work

• Combining probabilistic logic programming with the power of maximum entropy
• Markov logic networks
• Conditionals in nonmonotonic reasoning and belief revision. Considering conditionals as agents
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