Optimization of Stochastic Discrete Systems and Control on Complex Networks

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The book delves into advanced stochastic dynamic programming models and optimal control problems within networks, emphasizing new methods for discrete control issues and game variants of Markov decision problems. It begins by examining finite state spaces in Markov processes and existing algorithms, then introduces innovative dynamic programming and combinatorial techniques. Subsequent chapters focus on infinite horizon models, game-theoretical approaches, and finite horizon control problems, showcasing algorithms that significantly enhance computational network theory.