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ECML
2004
Springer
14 years 3 months ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
ICRA
1994
IEEE
94views Robotics» more  ICRA 1994»
14 years 2 months ago
A Reinforcement-Learning Approach to Reactive Control Policy Design for Autonomous Robots
Within the field of robotics, much recent attention has been given to control techniques that have been termed reactive or behavior-based. The design of such control systems for e...
Andrew H. Fagg, David Lotspeich, George A. Bekey
FSTTCS
2006
Springer
14 years 1 months ago
Testing Probabilistic Equivalence Through Reinforcement Learning
We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
Josee Desharnais, François Laviolette, Sami...
NIPS
1993
13 years 11 months ago
Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach
This paper describes the Q-routing algorithm for packet routing, in which a reinforcement learning module is embedded into each node of a switching network. Only local communicati...
Justin A. Boyan, Michael L. Littman
IJSNET
2006
145views more  IJSNET 2006»
13 years 10 months ago
RL-MAC: a reinforcement learning based MAC protocol for wireless sensor networks
:This paper introduces RL-MAC, a novel adaptive MediaAccess Control (MAC) protocol for Wireless Sensor Networks (WSN) that employs a reinforcement learning framework. Existing sche...
Zhenzhen Liu, Itamar Elhanany