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» Using Stochastic Grammars to Learn Robotic Tasks
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IROS
2009
IEEE
154views Robotics» more  IROS 2009»
15 years 6 months ago
Consideration on robotic giant-swing motion generated by reinforcement learning
—This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environme...
Masayuki Hara, Naoto Kawabe, Naoki Sakai, Jian Hua...
ICCV
2005
IEEE
15 years 5 months ago
Learning Non-Generative Grammatical Models for Document Analysis
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...
Michael Shilman, Percy Liang, Paul A. Viola
ICRA
2008
IEEE
119views Robotics» more  ICRA 2008»
15 years 6 months ago
Towards schema-based, constructivist robot learning: Validating an evolutionary search algorithm for schema chunking
— In this paper, we lay the groundwork for extending our previously developed ASyMTRe architecture to enable constructivist learning for multi-robot team tasks. The ASyMTRe archi...
Yifan Tang, Lynne E. Parker
111
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ICML
2007
IEEE
16 years 16 days ago
Cross-domain transfer for reinforcement learning
A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcemen...
Matthew E. Taylor, Peter Stone
NIPS
2008
15 years 1 months ago
Deep Learning with Kernel Regularization for Visual Recognition
In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Kai Yu, Wei Xu, Yihong Gong