A Probabilistic Extension of Action Language BC+
This work provides a formal framework for probabilistic reasoning in dynamic domains, but it is incremental as it extends an existing language without broad empirical validation.
The authors introduced pBC+, a probabilistic extension of the action language BC+, to model transition systems using LPMLN programs, enabling probabilistic reasoning for tasks like prediction, postdiction, planning, and diagnosis in dynamic domains.
We present a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we call pBC+, is defined as a high-level notation of LPMLN programs---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 in pBC+ and computed using an implementation of LPMLN.