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» A Reinforcement Learning Approach for Multiagent Navigation
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ICRA
2009
IEEE
138views Robotics» more  ICRA 2009»
15 years 4 months ago
Which landmark is useful? Learning selection policies for navigation in unknown environments
Abstract— In general, a mobile robot that operates in unknown environments has to maintain a map and has to determine its own location given the map. This introduces significant...
Hauke Strasdat, Cyrill Stachniss, Wolfram Burgard
WECWIS
2003
IEEE
120views ECommerce» more  WECWIS 2003»
15 years 3 months ago
Reinforcement Learning Applications in Dynamic Pricing of Retail Markets
In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative mode...
C. V. L. Raju, Y. Narahari, K. Ravikumar
GECCO
2000
Springer
142views Optimization» more  GECCO 2000»
15 years 1 months ago
Controlling Effective Introns for Multi-Agent Learning by Genetic Programming
This paper presents the emergence of the cooperative behavior for multiple agents by means of Genetic Programming (GP). For the purpose of evolving the effective cooperative behav...
Hitoshi Iba, Makoto Terao
ROBOCUP
2007
Springer
167views Robotics» more  ROBOCUP 2007»
15 years 4 months ago
Cooperative/Competitive Behavior Acquisition Based on State Value Estimation of Others
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
Kentarou Noma, Yasutake Takahashi, Minoru Asada
ICRA
2010
IEEE
117views Robotics» more  ICRA 2010»
14 years 8 months ago
Learning reliable and efficient navigation with a humanoid
Reliable and efficient navigation with a humanoid robot is a difficult task. First, the motion commands are executed rather inaccurately due to backlash in the joints or foot slipp...
Stefan Oßwald, Armin Hornung, Maren Bennewit...