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ESANN
2008
13 years 9 months ago
Multilayer Perceptrons with Radial Basis Functions as Value Functions in Reinforcement Learning
Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...
Victor Uc Cetina
TSMC
2008
229views more  TSMC 2008»
13 years 7 months ago
A Comprehensive Survey of Multiagent Reinforcement Learning
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
Lucian Busoniu, Robert Babuska, Bart De Schutter
ICRA
2007
IEEE
155views Robotics» more  ICRA 2007»
14 years 2 months ago
Value Function Approximation on Non-Linear Manifolds for Robot Motor Control
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
Masashi Sugiyama, Hirotaka Hachiya, Christopher To...
ICONIP
2010
13 years 6 months ago
Learning Basis Representations of Inverse Dynamics Models for Real-Time Adaptive Control
Abstract. In this paper, we propose a novel approach for adaptive control of robotic manipulators. Our approach uses a representation of inverse dynamics models learned from a vari...
Yasuhito Horiguchi, Takamitsu Matsubara, Masatsugu...
IBERAMIA
2004
Springer
14 years 1 months ago
Mobile Robotic Supported Collaborative Learning (MRSCL)
In this paper we describe MRSCL Geometry a collaborative educational activity that explores the use of robotic technology and wirelessly connected Pocket PCs as tools for teaching ...
Rubén Mitnik, Miguel Nussbaum, Alvaro Soto