New Advances in Logic-Based Probabilistic Modeling by PRISM

DOI10.1007/978-3-540-78652-8_5zbMath1137.68617OpenAlexW2100145144MaRDI QIDQ5452024

Taisuke Sato, Yoshitaka Kameya

Publication date: 28 March 2008

Published in: Probabilistic Inductive Logic Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-78652-8_5

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic programming (68N17)

Related Items (14)

Probabilistic abductive logic programming using Dirichlet priors ⋮ Unnamed Item ⋮ PR-OWL - a language for defining probabilistic ontologies ⋮ A new probabilistic constraint logic programming language based on a generalised distribution semantics ⋮ Constraint-based probabilistic modeling for statistical abduction ⋮ Learning failure-free PRISM programs ⋮ ILP turns 20. Biography and future challenges ⋮ Unnamed Item ⋮ Learning to rank in PRISM ⋮ Lifted Bayesian Filtering in Multiset Rewriting Systems ⋮ Negative probabilities in probabilistic logic programs ⋮ Inference with constrained hidden Markov models in PRISM ⋮ A Survey of Directed Entity-Relation--Based First-Order Probabilistic Languages ⋮ Logic-Based Probabilistic Modeling

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