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ROBOCUP
2007
Springer
167views Robotics» more  ROBOCUP 2007»
14 years 1 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
MICAI
2009
Springer
14 years 2 months ago
A Two-Stage Relational Reinforcement Learning with Continuous Actions for Real Service Robots
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
Julio H. Zaragoza, Eduardo F. Morales
AAAI
2000
13 years 9 months ago
Localizing Search in Reinforcement Learning
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Gregory Z. Grudic, Lyle H. Ungar
ICML
2010
IEEE
13 years 8 months ago
Nonparametric Return Distribution Approximation for Reinforcement Learning
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashim...
ATAL
2007
Springer
14 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone