Inference in probabilistic logic programs with continuous random variables

DOI10.1017/S1471068412000154zbMath1260.68063arXiv1112.2681MaRDI QIDQ4911131

I. V. Ramakrishnan, Muhammad Asiful Islam, C. R. Ramakrishnan

Publication date: 13 March 2013

Published in: Theory and Practice of Logic Programming (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1112.2681

zbMATH Keywords

discrete-valued random variablesGamma-distributed random variablesGaussian-distributed random variablessymbolic inference procedure

Mathematics Subject Classification ID

Logic programming (68N17)

Related Items (5)

Learning Probabilistic Logic Programs over Continuous Data ⋮ Learning Distributional Programs for Relational Autocompletion ⋮ A new probabilistic constraint logic programming language based on a generalised distribution semantics ⋮ A semantics for hybrid probabilistic logic programs with function symbols ⋮ Structured learning modulo theories

Uses Software

• ProbLog
• PRMLT

Cites Work

• Probabilistic Horn abduction and Bayesian networks
• The semantics of constraint logic programs1Note that reviewing of this paper was handled by the Editor-in-Chief.1

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