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Markov 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...
Often, real-world problems modeled by Markov decision processes (MDPs) are difficult to solve in practise because of the curse of dimensionality. In others, explicit specification of the MDP model parameters is not feasible, but simulation samples are available. For...
Saul Gass has been a leading contributor to the field of Operations Research for more than 50 years. He has been affiliated with the Robert H. Smith School of Business at the University of Maryland for more than 30 years. On February 25, 2006, "Operations Research in...
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