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IJCAI
2001
13 years 10 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
ISLPED
1999
ACM
91views Hardware» more  ISLPED 1999»
14 years 1 months ago
Stochastic modeling of a power-managed system: construction and optimization
-- The goal of a dynamic power management policy is to reduce the power consumption of an electronic system by putting system components into different states, each representing ce...
Qinru Qiu, Qing Wu, Massoud Pedram
IJRR
2008
73views more  IJRR 2008»
13 years 8 months ago
Optimization of Complex Robot Applications under Real Physical Limitations
This paper deals with minimum time trajectory optimization along a specified path subject to thermal constraints. We point out here that robots are often integrated in complex rob...
Matthieu Guilbert, Luc D. Joly, Pierre-Brice Wiebe...
INFOCOM
2003
IEEE
14 years 2 months ago
On-line Tuning of Prices for Network Services
— Recent investigations into the pricing of multiclass loss networks have shown that static prices are optimal in the asymptotic regime of many small sources. These results sugge...
Enrique Campos-Náñez, Stephen D. Pat...
ICDCS
2010
IEEE
14 years 20 days ago
Stochastic Steepest-Descent Optimization of Multiple-Objective Mobile Sensor Coverage
—We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the ...
Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Na...