… electric water heaters and proposes a deep reinforcement learning method to optimize the
… based on deep reinforcement learning for demand response using electric water heaters. …

… , cloud computing brings greater capabilities and opportunities for recent IT resource utilization.
As the core of cloud computing, intelligent cloud … DRL Reinforcement learning is an area …

… is a new paradigm to offer dynamic, reliable and elastic computing services. Efficient …
emerging Cloud computing. Considering the growing complexity of Cloud computing, future Cloud …

… DQN is a deep reinforcement learning (DRL) approach that employs neural networks to …
approaches in cloud computing. We also survey the main deep and reinforcement learning-…

… architecture of cloud computing, which includes user, cloud broker… , we present a deep
reinforcement learning model. Finally, a … 3 presents proposed deep reinforcement learning based …

… Resource allocation is an important task in cloud computing so that a standard trade-off
could be established. This research article proposed a fair scheduling deep reinforcement …

… Therefore, we want to use a deep neural network in combination with reinforcement … problems
in cloud computing. Therefore, we have used a Deep Reinforcement Learning model [39] …

… In this work we use Deep Reinforcement learning techniques … a Deep Reinforcement
learning agent, called DERP (Deep … We compare our agent to state-of-the-art, Reinforcement …

… DLS and DRLS: this paper utilizes deep learning (DL) and deep reinforcement learning (DRL)
respectively to represent the decision-making process of selecting scheduling algorithm …

… We provide an RL model of the Spark job scheduling problem in cloud computing environments.
We also formulate the rewards to train DRL-based agents to satisfy resource constraints…