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IJRR
2008
186views more  IJRR 2008»
15 years 6 months ago
Automated Design of Adaptive Controllers for Modular Robots using Reinforcement Learning
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Paulina Varshavskaya, Leslie Pack Kaelbling, Danie...
NLE
2008
140views more  NLE 2008»
15 years 6 months ago
Active learning and logarithmic opinion pools for HPSG parse selection
For complex tasks such as parse selection, the creation of labelled training sets can be extremely costly. Resource-efficient schemes for creating informative labelled material mu...
Jason Baldridge, Miles Osborne
BC
2005
71views more  BC 2005»
15 years 6 months ago
The spatiotemporal learning rule and its efficiency in separating spatiotemporal patterns
The hippocampus plays an important role in the course of establishing long-term memory, i.e., to make short-term memory of spatially and temporally associated input information. In...
M. Tsukada, X. Pan
JMLR
2002
125views more  JMLR 2002»
15 years 6 months ago
Lyapunov Design for Safe Reinforcement Learning
Lyapunov design methods are used widely in control engineering to design controllers that achieve qualitative objectives, such as stabilizing a system or maintaining a system'...
Theodore J. Perkins, Andrew G. Barto
TNN
1998
111views more  TNN 1998»
15 years 6 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos