Modeling Stochastic Control Optimization And Applications
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REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, in
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This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production
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As is well known, Pontryagin's maximum principle and Bellman's dynamic programming are the two principal and most commonly used approaches in solving stochastic
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