- Yi Wu, Lei Li, Stuart J. Russell. 2014. BFiT: From Possible-World Semantics to Random-Evaluation Semantics in an Open Universe. Abstract: In recent years, several probabilistic programming languages (PPLs) have emerged, such as Bayesian Logic (BLOG), Church, and Figaro. These languages can be classified into two categories: PPLs interpreted using possible-world semantics and ones using random-evaluation semantics. In this paper, we explicitly analyze the equivalence between these two semantics in the context of openuniverse probability models (OUPMs). We propose a novel dynamic memoization technique to construct OUPMs using procedural instructions in random-evaluation based PPLs. We implemented a translator named BFiT, which converts code in BLOG (possible-world based) to Figaro (random-evaluation based). The translated program in Figaro exhibits a merely constant blowup factor in program size while yielding the same inference results as the original model in BLOG.
