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HCW
1999
IEEE
13 years 12 months ago
Multiple Cost Optimization for Task Assignment in Heterogeneous Computing Systems Using Learning Automata
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Raju D. Venkataramana, N. Ranganathan
EURONGI
2005
Springer
14 years 1 months ago
An Afterstates Reinforcement Learning Approach to Optimize Admission Control in Mobile Cellular Networks
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
José Manuel Giménez-Guzmán, J...
UAI
2001
13 years 9 months ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao
IJRR
2008
151views more  IJRR 2008»
13 years 7 months ago
Trajectory Optimization using Reinforcement Learning for Map Exploration
Automatically building maps from sensor data is a necessary and fundamental skill for mobile robots; as a result, considerable research attention has focused on the technical chall...
Thomas Kollar, Nicholas Roy
JUCS
2008
104views more  JUCS 2008»
13 years 7 months ago
Optimal Transit Price Negotiation: The Distributed Learning Perspective
: We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmi...
Dominique Barth, Loubna Echabbi, Chahinez Hamlaoui