72 search results - page 11 / 15 » Continuous-Time Hierarchical Reinforcement Learning |
GECCO
2005
Springer
14 years 3 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...
IROS
2006
IEEE
14 years 3 months ago
2006
IEEE
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
CVPR
2011
IEEE
13 years 6 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...
AAAI
2008
14 years 4 days ago
2008
Hierarchical state decompositions address the curse-ofdimensionality in Q-learning methods for reinforcement learning (RL) but can suffer from suboptimality. In addressing this, w...
IEEEPACT
2008
IEEE
14 years 4 months ago
2008
IEEE
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...