Prior knowledge for learning networks in non-probabilistic settings

DOI10.1016/S0888-613X(99)00046-8zbMath0995.68111OpenAlexW2059489519MaRDI QIDQ1605682

Ramón Sangüesa, Ulises Cortés

Publication date: 23 July 2002

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

Full work available at URL: https://doi.org/10.1016/s0888-613x(99)00046-8

zbMATH Keywords

causal networkscurrent learning methods

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Knowledge representation (68T30) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

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• Classification of possibilistic uncertainty and information functions
• A Bayesian method for the induction of probabilistic networks from data
• Learning Bayesian networks: The combination of knowledge and statistical data
• ON THE NOTION OF DISTANCE REPRESENTING INFORMATION CLOSENESS: Possibility and Probability Distributions
• Approximating discrete probability distributions with dependence trees
• On Information and Sufficiency

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