… contextual bandit (CB) framework with continuous state and action spaces called deep
contextual bandit-oriented deep … The second is an innovative deep reinforcement learning (DRL) …

… deep reinforcement learning (DRL)-based DDPG approach. We have considered an actor-critic
agent where the critic is trained to learn … of IRS-assisted MS MU-MIMO communications. …

… In this work, we propose a deep reinforcement learning (DRL)-… Section III introduces the
IRS-assisted MS MU MIMO system … Debbah, “Deep contextual bandits for orchestrating multi-…

… Another straightforward approach to incorporate deep learning into the contextual bandits’
formulation would be via a reward-prediction ANN. Such a network accepts an observation …

… like deep reinforcement learning (DRL) and deep contextual … for IRSassisted multi-stream
multi-user MIMO (MS MU-MIMO) … to the deep contextual bandit-oriented deep deterministic …

… Debbah, “Deep contextual bandits for orchestrating multi-user miso systems with multiple …
and reinforcement learning for irs-assisted mu-mimo systems,” TechRxiv. Preprint. https://doi…

… the system sum-rate for each channel realization using reinforcement learning strategies. …
work considers an IRS-aided wideband MU MIMO system with a passive IRS and imperfect CSI…

… Debbah, "Deep contextual bandits for orchestrating multi-user MISO … Castedo, "Deep
contextual bandit and reinforcement learning for IRS-assisted MU-MIMO systems" TechRxiv. …

… , the author demonstrates IRS-assisted target … reinforcement learning and the karmed
bandit problem. The author in [52] demonstrated a new framework called deep contextual bandit-…

… of multi-user MIMO (MU-MIMO) at mmWave and especially THz frequencies. … of the
average bit rate and proposed a deep reinforcement learning (DRL) algorithm for its solution. …