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In this paper, an optimal control problem over a "hybrid Markov chain" (HMC) is studied. An HMC can be thought of as a traditional MC with continuous time dynamics pertaining to each node; from a different perspective, it can be regarded as a class of hybrid system with random discrete switches induced by an embedded MC. As a consequence of this setting, the index to be maximized, which depends on the dynamics, is the expected value of a nondeterministic cost function. After obtaining a closed form for the objective function, we gradually suggest how to device a computationally tractable algorithm to get to the optimal value. Furthermore, the complexity and rate of convergence of the algorithm is analyzed. Proofs and simulations of our results are provided; moreover, an applicative and motivating example is introduced.