163 search results - page 18 / 33 » Policy Gradient Methods for Robotics |
125
Voted
ICRA
2010
IEEE
15 years 9 days ago
2010
IEEE
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
122
click to vote
HRI
2007
ACM
15 years 5 months ago
2007
ACM
Learning by demonstration can be a powerful and natural tool for developing robot control policies. That is, instead of tedious hand-coding, a robot may learn a control policy by ...
114
click to vote
AAAI
2008
15 years 4 months ago
2008
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
142
click to vote
GECCO
2009
Springer
14 years 11 months ago
2009
Springer
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
113
click to vote
ICRA
2008
IEEE
15 years 8 months ago
2008
IEEE
Abstract— The widespread success of sampling-based planning algorithms stems from their ability to rapidly discover the connectivity of a configuration space. Past research has ...