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ICAC
2008
IEEE
15 years 4 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 3 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 4 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 9 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 1 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