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» Learning for Dynamic Subsumption
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TSMC
2002
100views more  TSMC 2002»
15 years 2 months ago
Repetitive learning control: a Lyapunov-based approach
In this paper, a learning-based feedforward term is developed to solve a general control problem in the presence of unknown nonlinear dynamics with a known period. Since the learn...
Warren E. Dixon, Erkan Zergeroglu, Darren M. Dawso...
127
Voted
AAAI
2000
15 years 4 months ago
Inter-Layer Learning Towards Emergent Cooperative Behavior
As applications for artificially intelligent agents increase in complexity we can no longer rely on clever heuristics and hand-tuned behaviors to develop their programming. Even t...
Shawn Arseneau, Wei Sun, Changpeng Zhao, Jeremy R....
132
Voted
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...
137
Voted
ICML
1996
IEEE
15 years 6 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
108
Voted
ICIP
2006
IEEE
16 years 4 months ago
Aggregated Dynamic Background Modeling
Standard practices in background modeling learn a separate model for every pixel in the image. However, in dynamic scenes the connection between an observation and the place where...
Amit Adam, Ehud Rivlin, Ilan Shimshoni