A Probabilistic Extension of Action Language
Joohyung Lee, Yi Wang · Theory and Practice of Logic Programming · 2018
Abstract We present a probabilistic extension of action language ${\cal BC}$+$ . Just like ${\cal BC}$+$ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we callp ${\cal BC}$+$ , is defined as a high-level notation of LPMLNprograms—a probabilistic extension of answer set programs. We show how probabilistic reasoning about transition systems, such as prediction, postdiction, and planning problems, as well as probabilistic diagnosis for dynamic domains, can be modeled inp ${\cal BC}$+$ and computed using an implementation of LPMLN.