Game Theory and Deep Learning : Fundamentals and Applications

311.21 SGD
会員価格
280.09
English

Product Description

Game Theory and Deep Learning: Fundamentals and Applications is the first book to establish a clear and comprehensive link between game theory and deep learning, demonstrating the critical importance of this interplay for solving key technological challenges such as those found in future wireless and energy networks. It delves into the latest connections between game theory and generative AI, including large language models, showcasing how these advanced concepts can be harnessed to address complex real-world problems. Readers will gain a deep understanding of how these two powerful fields intersect and the practical applications of this knowledge. The book teaches readers how to develop a solid foundation in game theory and understand interactive scenarios in both engineering and everyday life, effectively apply their knowledge to practical problems, including resource allocation, security, and influence maximization, and finally, design strategies that optimally exploit available information through successive optimization, reinforcement learning, deep learning, and generative AI techniques.

This groundbreaking book is the first to establish a clear and comprehensive link between game theory and deep learning, demonstrating the critical importance of this interplay for solving key technological challenges such as those found in future wireless and energy networks. It delves into the latest connections between game theory and generative AI, including large language models, showcasing how these advanced concepts can be harnessed to address complex real-world problems. Readers will gain a deep understanding of how these two powerful fields intersect and the practical applications of this knowledge, making it an essential resource for anyone looking to stay at the forefront of technological innovation.

With this book the reader will be able to: Develop a solid foundation in game theory and understand interactive scenarios in both engineering and everyday life; Effectively apply their knowledge to practical problems, including resource allocation, security, and influence maximization; Design strategies that optimally exploit available information through successive optimization, reinforcement learning, deep learning, and generative AI techniques.

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