"This book provides fundamental background on Deep Reinforcement Learning (DRL) and then studies recent advances in DRL to address practical challenges in wireless communications and networking. In particular, this book first gives a tutorial of DRL from basic concepts to advanced modelling techniques to motivate and provide fundamental knowledge for the readers. The authors then provide case studies together with implementation details to help readers better understand how to practice and apply DRL to their problems. After ...
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"This book provides fundamental background on Deep Reinforcement Learning (DRL) and then studies recent advances in DRL to address practical challenges in wireless communications and networking. In particular, this book first gives a tutorial of DRL from basic concepts to advanced modelling techniques to motivate and provide fundamental knowledge for the readers. The authors then provide case studies together with implementation details to help readers better understand how to practice and apply DRL to their problems. After that, they review DRL approaches that address emerging issues in communications and networking. Finally, the authors highlight important challenges, open issues, and future research directions of applying DRL in wireless networks."--
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