111 search results - page 3 / 23 » Reinforcement Learning for Operational Space Control |
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
NIPS
1994
13 years 8 months ago
1994
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
ICRA
2009
IEEE
14 years 2 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...
NIPS
2007
13 years 8 months ago
2007
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
NIPS
1997
13 years 8 months ago
1997
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...