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ICAC
2006
IEEE
15 years 4 months ago
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
ATAL
2009
Springer
15 years 4 months ago
Learning of coordination: exploiting sparse interactions in multiagent systems
Creating coordinated multiagent policies in environments with uncertainty is a challenging problem, which can be greatly simplified if the coordination needs are known to be limi...
Francisco S. Melo, Manuela M. Veloso
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
15 years 2 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
78
Voted
KBS
2006
105views more  KBS 2006»
14 years 10 months ago
Robot docking based on omnidirectional vision and reinforcement learning
We present a system for visual robotic docking using an omnidirectional camera coupled with the actor critic reinforcement learning algorithm. The system enables a PeopleBot robot...
David Muse, Cornelius Weber, Stefan Wermter
ATAL
2004
Springer
15 years 3 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