Markov Decision Processes and Stochastic Positional Games

<p>This book presents recent findings and results concerning the solutions of especially finite state-space Markov decision problems and determining Nash equilibria for related stochastic games with average and total expected discounted reward payoffs. In addition, it focuses on a new class of stochastic games: stochastic positional games that extend and generalize the classic deterministic positional games. It presents new algorithmic results on the suitable implementation of quasi-monotonic programming techniques. Moreover, the book presents applications of positional games within a class of multi-objective discrete control problems and hierarchical control problems on networks.</p><p> </p><p>Given its scope, the book will benefit all researchers and graduate students who are interested in Markov theory, control theory, optimization and games.</p><p></p>