Combining Logical and Probabilistic Reasoning
نویسندگان
چکیده
This paper describes a family of knowledge representation problems, whose intuitive solutions require reasoning about defaults, the effects of actions, and quantitative probabilities. We describe an extension of the probabilistic logic language P-log (Baral & Gelfond & Rushton 2004), which uses “consistency restoring rules” to tackle the problems described. We also report the results of a preliminary investigation into the efficiency of our P-log implementation, as compared with ACE(Chavira & Darwiche & Jaeger 2004), a system developed by Automated Reasoning Group at UCLA.
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