Probabilistic abductive logic programming using Dirichlet priors

DOI10.1016/j.ijar.2016.07.001zbMath1386.68163OpenAlexW2467782716MaRDI QIDQ324690

Luke Dickens, Calin Rares Turliuc, Alessandra Russo, Krysia Broda

Publication date: 17 October 2016

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

Full work available at URL: https://doi.org/10.1016/j.ijar.2016.07.001

zbMATH Keywords

Markov chain Monte Carloprobabilistic programmingabductive logic programminglatent Dirichlet allocationrepeated insertion model

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Logic in artificial intelligence (68T27) Logic programming (68N17)

Related Items (1)

The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference

Uses Software

• ProbLog
• BUGS
• Church
• Stan
• SICStus
• Figaro

Cites Work

• The repeated insertion model for rankings: missing link between two subset choice models
• On Minimality and Integrity Constraints in Probabilistic Abduction
• Hierarchical Dirichlet Processes
• A kripke-kleene semantics for logic programs*
• Graph-Based Algorithms for Boolean Function Manipulation
• Binary Decision Diagrams
• Inference and learning in probabilistic logic programs using weighted Boolean formulas
• 10.1162/jmlr.2003.3.4-5.993
• Abductive Logic Programming
• New Advances in Logic-Based Probabilistic Modeling by PRISM

This page was built for publication: Probabilistic abductive logic programming using Dirichlet priors