575 search results - page 57 / 115 » Reinforcement Learning State Estimator |
130
Voted
UAI
2008
15 years 1 months ago
2008
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
100
Voted
ATAL
2008
Springer
15 years 2 months ago
2008
Springer
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
101
Voted
ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
88
Voted
ICML
2001
IEEE
16 years 1 months ago
2001
IEEE
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
107
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ICRA
2007
IEEE
15 years 6 months ago
2007
IEEE
Abstract— Particle filters have been applied with great success to various state estimation problems in robotics. However, particle filters often require extensive parameter tw...