Probabilistic Reasoning With Answer Sets

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 nontrivial 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.

• Type: Conference
• Year: 2004
• Where: LPNMR
• Authors: Chitta Baral, Michael Gelfond, J. Nelson Rushton
• Keywords: Answer Set Prolog, Bayes Nets, Causal Bayes Nets, LPNMR 2004