Probabilistic reasoning with answer sets

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This paper develops a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Answer Set Prolog is used as the logical foundation, while causal Bayes nets serve as a probabilistic foundation. We give several non-trivial examples and illustrate the use of P-log for knowledge representation and updating of knowledge. We argue that our approach to updates is more appealing than existing approaches. We give sufficiency conditions for the coherency of P-log programs and show that Bayes nets can be easily mapped to coherent P-log programs.
77 pages. To appear in Theory and Practice of Logic Programming (TPLP)

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Artificial Intelligence, Logic in Computer Science

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http://salesiana.dossiersoluciones.com/handle/123456789/209422

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0812.0659
 http://arxiv.org/abs/0812.0659

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arXiv