作者: Luc De Raedt , Angelika Kimmig , Hannu Toivonen , None
DOI:
关键词: Programming language 、 Context (language use) 、 Theoretical computer science 、 Solver 、 Binary decision diagram 、 Semantics (computer science) 、 Probabilistic programming language 、 Computer science 、 Semantics 、 Probabilistic logic 、 Iterative deepening depth-first search 、 Prolog
摘要: We introduce ProbLog, a probabilistic extension of Prolog. A ProbLog program defines distribution over logic programs by specifying for each clause the probability that it belongs to randomly sampled program, and these probabilities are mutually independent. The semantics is then defined success query, which corresponds query succeeds in program. key contribution this paper introduction an effective solver computing probabilities. It essentially combines SLD-resolution with methods Boolean formulae. Our implementation further employs approximation algorithm iterative deepening binary decision diagrams. report on experiments context discovering links real biological networks, demonstration practical usefulness approach.