We extend probabilistic action language $p{\cal BC}$ + with the notion of utility in decision theory. The semantics of the extended $p{\cal BC}$ + can be defined as a shorthand notation for a decision-theoretic extension of the probabilistic answer set programming language LPMLN. Alternatively, the semantics of $p{\cal BC}$ + 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 leveraging an MDP solver to compute a $p{\cal BC}$ + action description. The idea led to the design of the system pbcplus2mdp, which can find an optimal policy of a $p{\cal BC}$ + action description using an MDP solver.