Tangential hand velocity profiles of rapid human arm movements often appear as sequences of several bell-shaped acceleration-deceleration phases called submovements or movement un...
Markov Decision Processes (MDPs) have been extensively studied and used in the context of planning and decision-making, and many methods exist to find the optimal policy for probl...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
customer which exceeds its deadline will either leave the queue without service or stay in the queue to get unsucWe consider the problem of scheduling impatient CUS- cessful servic...
Zheng-Xue Zhao, Shivendra S. Panwar, Donald F. Tow...
Abstract. We present a first constant performance guarantee for preemptive stochastic scheduling to minimize the sum of weighted completion times. For scheduling jobs with release ...
Abstract—This paper presents a model and theory for streaming layered video. We model the bandwidth available to the streaming application as a stochastic process whose statistic...
Optimal behavior is a very desirable property of autonomous agents and, as such, has received much attention over the years. However, making optimal decisions and executing optima...
ACT We consider an optimal power and rate scheduling problem for a single user transmitting to a base station on a fading wireless link with the objective of minimizing the mean de...
— This paper addresses learning based adaptive resource allocation for wireless MIMO channels with Markovian fading. The problem is posed as Constrained Markov Decision Process w...
— In this paper, we use the Markov Decision Process (MDP) technique to find the optimal code allocation policy in High-Speed Downlink Packet Access (HSDPA) networks. A discrete ...
Hussein Al-Zubaidy, Jerome Talim, Ioannis Lambadar...