Titlebook: Simulation-Based Algorithms for Markov Decision Processes; Hyeong Soo Chang,Jiaqiao Hu,Steven I. Marcus Book 2013Latest edition Springer-V

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Hyeong Soo Chang,Jiaqiao Hu,Michael C. Fu,Steven I. Marcusschon ein mehr oder weniger vages Bild voneinander gemacht. Für die folgenden Überlegungen stellen wir uns einen Patienten vor, der sich telefonisch oder schriftlich angemeldet hat. Er hat seine Probleme kurz erwähnt oder einen langen Lebenslauf geschrieben, um die Dringlichkeit einer Konsultation z

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0178-5354 nty that new results will have a sound foundation.New chapteMarkov 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

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Markov Decision Processes,mmarizing the associated optimality equations. We then present the well-known exact solution algorithms, value iteration and policy iteration, and outline a framework of rolling-horizon control (also called receding-horizon control) as an approximate solution methodology for solving MDPs, in conjunc

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Multi-stage Adaptive Sampling Algorithms,state spaces, where the usual techniques of policy iteration and value iteration are either computationally impractical or infeasible to implement. We present two adaptive sampling algorithms that estimate the optimal value function by choosing actions to sample in each state visited on a finite-hor

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