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» Action discovery for reinforcement learning
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PPSN
2004
Springer
14 years 1 months ago
Evolutionary Multi-agent Systems
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
Pieter Jan't Hoen, Edwin D. de Jong
TSMC
2008
117views more  TSMC 2008»
13 years 6 months ago
Discovery of High-Level Behavior From Observation of Human Performance in a Strategic Game
This paper explores the issues faced in creating a sys-4 tem that can learn tactical human behavior merely by observing5 a human perform the behavior in a simulation. More specific...
Brian S. Stensrud, Avelino J. Gonzalez
AVSS
2006
IEEE
14 years 1 months ago
Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments
In this paper we report on techniques for automatically learning foveal sensing strategies for an active pan-tiltzoom camera. The approach uses reinforcement learning to discover ...
Andrew D. Bagdanov, Alberto Del Bimbo, Walter Nunz...
ICRA
2010
IEEE
117views Robotics» more  ICRA 2010»
13 years 5 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...
ATAL
2010
Springer
13 years 8 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko