199 search results - page 3 / 40 » Efficient Reinforcement Learning with Relocatable Action Mod... |
ICML
1998
IEEE
14 years 8 months ago
1998
IEEE
tion Learning about Temporally Abstract Actions Richard S. Sutton Department of Computer Science University of Massachusetts Amherst, MA 01003-4610 rich@cs.umass.edu Doina Precup D...
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...
ESANN
2008
13 years 9 months ago
2008
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
ICANN
2010
Springer
13 years 8 months ago
2010
Springer
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...