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» Using model knowledge for learning inverse dynamics
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138
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IROS
2007
IEEE
168views Robotics» more  IROS 2007»
15 years 9 months ago
Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
140
Voted
ESANN
2004
15 years 4 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
VLSID
2004
IEEE
120views VLSI» more  VLSID 2004»
16 years 3 months ago
Dynamic Power Optimization of Interactive Systems
Abstract-- Power has become a major concern for mobile computing systems such as laptops and handhelds, on which a significant fraction of software usage is interactive instead of ...
Lin Zhong, Niraj K. Jha
157
Voted
ASC
2004
15 years 3 months ago
Soft computing applications in dynamic model identification of polymer extrusion process
This paper proposes the applications of soft computing to deal with the constraints in conventional modelling techniques of the dynamic extrusion process. The proposed technique i...
Leong Ping Tan, Ahmad Lotfi, Eugene Lai, J. B. Hul...
144
Voted
ATAL
2011
Springer
14 years 3 months ago
Learning action models for multi-agent planning
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
Hankz Hankui Zhuo, Hector Muñoz-Avila, Qian...