Optimization of Stochastic Discrete Systems and Control on Complex Networks

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Focusing on stochastic dynamic programming, this book explores optimal control problems within networks, presenting innovative findings on discrete optimal control and game variants of Markov decision problems. It begins with a review of finite state space Markov processes and existing algorithms, then introduces new dynamic programming and combinatorial methods. Subsequent chapters address infinite horizon models, game-theoretical approaches, and finite horizon stochastic control problems, offering valuable algorithms that enhance computational network theory.