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» UMAS Learning Requirement for Controlling Network Resources
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AIPS
2004
13 years 6 months ago
Trading Places: How to Schedule More in a Multi-Resource Oversubscribed Scheduling Problem
Oversubscribed scheduling problems require removing tasks when enough resources are not available. Prior AI approaches have mostly been constructive or repairbased heuristic searc...
Laura Barbulescu, Adele E. Howe, L. Darrell Whitle...
ATAL
2004
Springer
13 years 10 months ago
Resource Allocation in the Grid Using Reinforcement Learning
One of the main challenges in Grid computing is efficient allocation of resources (CPU-hours, network bandwidth, etc.) to the tasks submitted by users. Due to the lack of centrali...
Aram Galstyan, Karl Czajkowski, Kristina Lerman
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
13 years 11 months ago
Q-RAN: A Constructive Reinforcement Learning Approach for Robot Behavior Learning
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
Jun Li, Achim J. Lilienthal, Tomás Mart&iac...
ICNP
2005
IEEE
13 years 11 months ago
CONNET: Self-Controlled Access Links for Delay and Jitter Requirements
Access links are typically the bottleneck between a high bandwidth LAN and a high bandwidth IP network. Without a priori resource provisioning or reservation, this tends to have a...
Mohamed A. El-Gendy, Kang G. Shin, Hosam Fathy
IOR
2010
94views more  IOR 2010»
13 years 2 months ago
Utility-Maximizing Resource Control: Diffusion Limit and Asymptotic Optimality for a Two-Bottleneck Model
We study a stochastic network that consists of two servers shared by two classes of jobs. Class 1 jobs require a concurrent occupancy of both servers while class 2 jobs use one se...
Heng-Qing Ye, David D. Yao