Titlebook: Reinforcement Learning for Reconfigurable Intelligent Surfaces; Assisted Wireless Co Alice Faisal,Ibrahim Al-Nahhal,Telex M. N. Ngatche Boo

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Applications of RL for Discrete Problems in RIS-Assisted Communication Systems, explores the application of DRL techniques, including Q-learning and DQL, to optimize RIS-assisted systems efficiently. It details how these algorithms can be adapted and formulated to tackle discrete optimization problems in different scenarios, taking into account various assumptions and system c

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Challenges and Future Work,ssing the challenges associated with DRL, particularly focusing on hyperparameter tuning and problem design. The chapter further provides insights into addressing these challenges effectively and presents three promising directions. First, it introduces the concept of hybrid RL, which combines RL wi

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2191-5768 apter 5, which introduces the challenges and future directions in this field. It explores the particulars of hyperparameter tuning, problem design, and complexi978-3-031-52553-7978-3-031-52554-4Series ISSN 2191-5768 Series E-ISSN 2191-5776

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