Game theory emerges as a mathematical framework for analyzing and optimizing decision-making in complex, interactive environments, making it well-suited for intelligent network control paradigms. As modern networks become autonomous, traditional control strategies struggle when addressing issues like resource allocation and conflict resolution. Game theory provides tools to model and predict strategic interactions among multiple intelligent agents within a network, enabling robust, adaptive, and efficient control mechanisms. This shift towards game-theoretic network control paves the way for self-organizing, scalable, and context-aware networks capable of meeting the demands of next-generation technologies. Game Theory for Intelligent Network Control Paradigm explores applications of game theory, current trends, understudied areas, and new directions for further investigation. It presents an introduction on game theory with an emphasis on applications for intelligent control issues. This book covers topics such as network control, cloud computing, and learning algorithms, and is a useful resource computer engineers, business owners, academicians, researchers, and scientists.
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