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Full Description
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.
Contents
1. Introduction
2. Overview of deep learning
3. Overview of game Theory
4. Conventional deep learning and game theory (GANs, VAE, DMs, CNN, RNN,...).
5. Federated learning and game theory
6. Reinforcement learning and game theory
7. Mean field games and deep learning
8. Large Language Models and game theory
9. Wireless resource allocation (6G applications)
10. Smart grid applications (power consumption scheduling, load forecast, real-time pricing,...)
11. Agent-Based LLMs and game-theoretic paradigms for security
