181 search results - page 17 / 37 » State Space Reduction For Hierarchical Reinforcement Learnin... |
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
CVPR
2011
IEEE
13 years 4 months ago
2011
IEEE
This paper tackles shape grammar parsing for facade segmentation using a novel optimization approach based on reinforcement learning (RL). To this end, we use a binary recursive g...
UAI
2008
13 years 9 months ago
2008
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
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...
AAAI
2006
13 years 9 months ago
2006
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...