Optimizing Probabilities in Probabilistic Logic Programs

Probabilistic Logic Programming is an effective formalism for encoding problems characterized by uncertainty. Some of these may require the optimization probability values subject to constraints among distributions random variables. Here, we introduce a new class probabilistic logic programs, namely Optimizable Programs, and provide algorithm find best assignment probabilities variables, such that set satisfied objective function optimized. This paper under consideration acceptance in Theory Practice Programming.