Probabilisitc Logic Programming under Maximum Entropy
- Cite this paper as:
- Lukasiewicz T., Kern-Isberner G. (1999) Probabilisitc Logic Programming under Maximum Entropy. In: Hunter A., Parsons S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1999. Lecture Notes in Computer Science, vol 1638. Springer, Berlin, Heidelberg
In this paper, we focus on the combination of probabilistic logic programming with the principle of maximum entropy. We start by defining probabilistic queries to probabilistic logic programs and their answer substitutions under maximum entropy. We then present an efficient linear programming characterization for the problem of deciding whether a probabilistic logic program is satisfiable. Finally, and as a central contribution of this paper, we introduce an efficient technique for approximative probabilistic logic programming under maximum entropy. This technique reduces the original entropy maximization task to solving a modified and relatively small optimization problem.
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