On the Coherence of Probabilistic Relational Formalisms

Autor(es)

De Bona, Glauber ^[1] ; Cozman, Fabio G. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Escola Politecn, BR-05508010 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Entropy; v. 20, n. 4 APR 2018.
• Citações Web of Science: 1

Resumo

There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian networks, while Relational Bayesian Networks (RBNs) employ first-order probability formulas with the same purpose. We examine the coherence checking problem for those formalisms; that is, the problem of guaranteeing that any grounding of a well-formed set of sentences does produce a valid Bayesian network. This is a novel version of de Finetti's problem of coherence checking for probabilistic assessments. We show how to reduce the coherence checking problem in relational Bayesian networks to a validity problem in first-order logic augmented with a transitive closure operator and how to combine this logic-based approach with faster, but incomplete algorithms. (AU)

• Processo FAPESP: 16/18841-0 - Algoritmos para inferência e aprendizado de programas lógicos probabilísticos
• Beneficiário: Fabio Gagliardi Cozman
• Linha de fomento: Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE
• Processo FAPESP: 16/25928-4 - Extensões probabilísticas de fragmentos da lógica de primeira ordem
• Beneficiário: Glauber de Bona
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado