Simulation-Based Algorithms for Markov Decision ProcessesMarkov decision process (MDP) models are widely used for modeling sequential decision making problems that arise in engineering, economics, computer science, and the social sciences. Many real world problems modeled by MDPs have huge state and or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable. In other cases, the system of interest is too complex to allow explicit