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ICAC
2008
IEEE
15 years 6 months ago
Utility-Based Reinforcement Learning for Reactive Grids
—Large scale production grids are an important case for autonomic computing. They follow a mutualization paradigm: decision-making (human or automatic) is distributed and largely...
Julien Perez, Cécile Germain-Renaud, Bal&aa...
ATAL
2005
Springer
15 years 5 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
IPPS
2009
IEEE
15 years 6 months ago
Power-aware dynamic task scheduling for heterogeneous accelerated clusters
Recent accelerators such as GPUs achieve better cost-performance and watt-performance ratio, while the range of their application is more limited than general CPUs. Thus heterogen...
Tomoaki Hamano, Toshio Endo, Satoshi Matsuoka
RTS
2002
113views more  RTS 2002»
14 years 11 months ago
Feedback-Feedforward Scheduling of Control Tasks
A scheduling architecture for real-time control tasks is proposed. The scheduler uses feedback from execution-time measurements and feedforward from workload changes to adjust the...
Anton Cervin, Johan Eker, Bo Bernhardsson, Karl-Er...
GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 3 months ago
Domain Knowledge and Representation in Genetic Algorithms for Real World Scheduling Problems
This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
Ioannis T. Christou, Armand Zakarian