109 search results - page 7 / 22 » Neural Reinforcement Learning Controllers for a Real Robot A... |
ROBOCUP
2000
Springer
14 years 3 days ago
2000
Springer
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
ICRA
2009
IEEE
14 years 3 months ago
2009
IEEE
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
CEC
2003
IEEE
14 years 1 months ago
2003
IEEE
We introduce a technique that allows a real robot to execute real-time learning, in which GP and RL are integrated. In our former research, we showed the result of an experiment wi...
IROS
2009
IEEE
14 years 3 months ago
2009
IEEE
—This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environme...
CEC
2009
IEEE
14 years 3 months ago
2009
IEEE
Abstract— In this paper we describe simulation of autonomous robots controlled by recurrent neural networks, which are evolved through indirect encoding using HyperNEAT algorithm...