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ADCM
2008
136views more  ADCM 2008»
15 years 4 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
CORR
2006
Springer
101views Education» more  CORR 2006»
15 years 4 months ago
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...
ML
2006
ACM
113views Machine Learning» more  ML 2006»
15 years 4 months ago
Learning to bid in bridge
Bridge bidding is considered to be one of the most difficult problems for game-playing programs. It involves four agents rather than two, including a cooperative agent. In additio...
Asaf Amit, Shaul Markovitch
142
Voted
TSMC
2008
132views more  TSMC 2008»
15 years 4 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
150
Voted
ICRA
2010
IEEE
153views Robotics» more  ICRA 2010»
15 years 3 months ago
Learning to navigate through crowded environments
— The goal of this research is to enable mobile robots to navigate through crowded environments such as indoor shopping malls, airports, or downtown side walks. The key research ...
Peter Henry, Christian Vollmer, Brian Ferris, Diet...