Learning failure-free PRISM programs

DOI10.1016/j.ijar.2015.06.003zbMath1344.68182OpenAlexW1590596319MaRDI QIDQ900370

James Cussens, Waleed Alsanie

Publication date: 22 December 2015

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

Full work available at URL: https://doi.org/10.1016/j.ijar.2015.06.003

zbMATH Keywords

prismstructure learningprobabilistic inductive logic programmingprobabilistic logic

Mathematics Subject Classification ID

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

Uses Software

• PRISM
• GlobalMIT

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimization by Simulated Annealing
• Variational Bayes via propositionalized probability computation in PRISM
• Learning context-free grammars from structural data in polynomial time
• Efficient learning of context-free grammars from positive structural examples
• Estimating the dimension of a model
• Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables
• Learning Bayesian networks: The combination of knowledge and statistical data
• Online Bayesian inference for the parameters of PRISM programs
• Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering
• Biological Sequence Analysis
• Metaheuristics for Hard Optimization
• New Advances in Logic-Based Probabilistic Modeling by PRISM
• Parameter estimation in stochastic logic programs

This page was built for publication: Learning failure-free PRISM programs