A Revised Comparison of Bayesian Logic Programs and Stochastic Logic Programs
نویسندگان
چکیده
This paper presents a revised comparison of Bayesian logic programs (BLPs) and stochastic logic programs (SLPs) based on a previous work. We first explore their semantical differences in terms of probabilistic logic learning settings and first-order probabilistic logics. We then revise BLP-SLP translations to resolve a potential ‘contradictory refutation’ problem. We finally work on the comparison of learnabilities of the two frameworks based on computational learning theory.
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