Elaboration Tolerant Representation of Markov Decision Process via
  Decision-Theoretic Extension of Probabilistic Action Language pBC+
  We extend probabilistic action language pBC+ with the notion of utility as in
decision theory. The semantics of the extended pBC+ can be defined as a
shorthand notation for a decision-theoretic extension of the probabilistic
answer set programming language LPMLN. Alternatively, the semantics of pBC+ can
also be defined in terms of Markov Decision Process (MDP), which in turn allows
for representing MDP in a succinct and elaboration tolerant way as well as to
leverage an MDP solver to compute pBC+. The idea led to the design of the
system pbcplus2mdp, which can find an optimal policy of a pBC+ action
description using an MDP solver. This paper is under consideration in Theory
and Practice of Logic Programming (TPLP).
