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IROS
2006
IEEE
113views Robotics» more  IROS 2006»
14 years 3 months ago
Policy Gradient Methods for Robotics
— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
Jan Peters, Stefan Schaal
AR
2002
157views more  AR 2002»
13 years 9 months ago
Acquiring state from control dynamics to learn grasping policies for robot hands
Abstract--A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the ...
Roderic A. Grupen, Jefferson A. Coelho Jr.
JAIR
2007
124views more  JAIR 2007»
13 years 9 months ago
Closed-Loop Learning of Visual Control Policies
In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-...
Sébastien Jodogne, Justus H. Piater
ICPR
2006
IEEE
14 years 10 months ago
Direct Mapping of Visual Input to Motor Torques
Most methods for visual control of robots formulate the robot command in joint or Cartesian space. To move the robot these commands are remapped to motor torques usually requiring...
Jeremiah J. Neubert, Nicola J. Ferrier
ESANN
2008
13 years 11 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