Strong Equivalence for LPMLN Programs
This work provides a mathematical tool for simplifying LPMLN programs, which is incremental as it builds on existing concepts in logic programming.
The paper tackles the problem of verifying strong equivalence in LPMLN programs, a probabilistic extension of answer set programs, by reducing it to equivalence checking in classical logic and the logic of here-and-there, enabling the use of answer set solvers for this task.
LPMLN is a probabilistic extension of answer set programs with the weight scheme adapted from Markov Logic. We study the concept of strong equivalence in LPMLN, which is a useful mathematical tool for simplifying a part of an LPMLN program without looking at the rest of it. We show that the verification of strong equivalence in LPMLN can be reduced to equivalence checking in classical logic via a reduct and choice rules as well as to equivalence checking under the "soft" logic of here-and-there. The result allows us to leverage an answer set solver for LPMLN strong equivalence checking. The study also suggests us a few reformulations of the LPMLN semantics using choice rules, the logic of here-and-there, and classical logic.