Abstract
AbstractWe 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.
Publisher
Cambridge University Press (CUP)
Subject
Artificial Intelligence,Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software
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