72 search results - page 11 / 15 » Continuous-Time Hierarchical Reinforcement Learning |
108
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GECCO
2005
Springer
15 years 8 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...
114
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IROS
2006
IEEE
15 years 9 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...
169
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CVPR
2011
IEEE
15 years 22 hour 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
15 years 5 months 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...
156
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IEEEPACT
2008
IEEE
15 years 9 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...