2.9AIJul 10, 2015
Lazy Explanation-Based Approximation for Probabilistic Logic ProgrammingJoris Renkens, Angelika Kimmig, Luc De Raedt
We introduce a lazy approach to the explanation-based approximation of probabilistic logic programs. It uses only the most significant part of the program when searching for explanations. The result is a fast and anytime approximate inference algorithm which returns hard lower and upper bounds on the exact probability. We experimentally show that this method outperforms state-of-the-art approximate inference.