Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution

Product information for Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution

Discover the groundbreaking insights in "Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution," available now at Springer Shop. This essential SpringerBrief tackles a sophisticated class of Markov games featuring Borel state and action spaces, where payoff functions may be unbounded. The analysis covers both discounted and average payoff criteria, providing a comprehensive theoretical framework. The core challenge addressed is the unknown distribution of the observable disturbance process, a sequence of independent, identically distributed random variables. Unlike traditional models, both players must engage in statistical estimation at each stage before selecting their actions. This innovative approach combines adaptive decision-making with real-time estimation, offering a fresh perspective on infinite-horizon strategic interactions. This book systematically presents the latest developments in merging statistical methods with dynamic game theory. It lays a solid theoretical foundation for constructing robust player strategies that adapt to learned distribution estimates. The included illustrative examples help clarify these advanced concepts, making the material accessible. For researchers and practitioners in stochastic control, game theory, and their applications, this volume is an indispensable reference. It bridges theoretical rigor with practical methodology, advancing the field significantly. Explore this pivotal work and other specialized titles at link.springer.com, your premier source for cutting-edge scientific and scholarly content. Springer Shop delivers the authoritative resources you need to stay at the forefront of your discipline.