Probabilistic reasoning with answer sets

Details Probabilistic reasoning with answer sets Probabilistic reasoning with answer sets

2008-12-03

arxiv.org/abs/0812.0659v1

Computer Science

Artificial Intelligence

77 pages. To appear in Theory and Practice of Logic Programming (TPLP)

Scientific paper

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.

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