Reasoning with Probabilities: Relating Weighted Model Counting and Probabilistic Model Checking

Abstract

Weighted model counting (WMC) and probabilistic model checking (PMC) are two well- established frameworks that are independently developed, the former for probabilistic inference, the latter traditionally for probabilistic verification, though recently also applied to inference. The formal relationship between the two frameworks, however, remains largely unexplored. In this paper, we lay the foundations for how they relate: we present (1) a mapping from cycle- free parametric Markov chains (pMCs) to arithmetic circuits (ACs), enabling the reduction of reachability probability computations in such pMCs to a weighted model counting problem on the corresponding ACs, and (2) a mapping from a subclass of arithmetic circuits -- with probabilistic semantics -- back to parametric Markov chains. We propose a detailed correspondence between the entities of WMC and PMC, and discuss how our mappings enable transferring optimization techniques such as bisimulation minimization across the frameworks.