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» Policy Gradient Methods for Robotics
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ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
14 years 2 months ago
Model-based and model-free reinforcement learning for visual servoing
— To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by b...
Amir Massoud Farahmand, Azad Shademan, Martin J&au...
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
ATAL
2007
Springer
14 years 2 months ago
Transfer via inter-task mappings in policy search reinforcement learning
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
RAS
2006
105views more  RAS 2006»
13 years 7 months ago
Reinforcement learning for quasi-passive dynamic walking of an unstable biped robot
A class of biped locomotion called Passive Dynamic Walking (PDW) has been recognized to be efficient in energy consumption and a key to understand human walking. Although PDW is s...
Kentarou Hitomi, Tomohiro Shibata, Yutaka Nakamura...
AAMAS
2007
Springer
13 years 8 months ago
Coordinating microscopic robots in viscous fluids
Multiagent control provides strategies for aggregating microscopic robots (“nanorobots”) in fluid environments relevant for medical applications. Unlike larger robots, viscou...
Tad Hogg