… joint resource optimization problem in the virtualized vehicular networks. We exploit deep
reinforcement learning … ence levels, and the resource allocation and scheduling solution in this …

… total future resource transfer cost. The key problem addressed in this paper is that of learning
U i ( s ) in the dynamic resource allocation setting. If project resource allocations are fixed, …

… hybrid learning method for resource valuation estimates, combining disparate strengths
of both reinforcement learning and model-based policies, within a dynamic server allocation …

… reinforcement learning (RL) techniques for the important problem of optimal online allocation
of resources… Data Center scenario for studying resource allocation, which generally follows …

… a learning agent and each resource allocation solution corresponds to an action taken by the
UAVs. Afterwards, we develop a multi-agent reinforcement learning (… using learning. More …

… reinforcement learning approaches to resource allocation and application support to
contextualise the contributions of this paper over previous automated control learning approaches. …

… introduce the reinforcement learning method and several strategies adopted in our proposed
resource allocation algorithm DRLRA. Then, we present the classical Q-learning and the …

… decentralized algorithm for resource allocation in a simplified … reinforcement learning agents
that share common resources … to a particular resource and which serves as a reinforcement …

… for resource allocation in CPS, which was based on a design of the reinforcement learning
… service level, which enabled a dynamic resource allocation and avoided a fixed input task …

… 342–343 (2005)) we showed the feasibility of using online RL to learn resource valuation
estimates (in lookup table form) which can be used to make high-quality server allocation …