360 search results - page 4 / 72 » Combining Learned Discrete and Continuous Action Models |
ICML
1996
IEEE
15 years 10 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
71
Voted
MICAI
2009
Springer
15 years 4 months ago
2009
Springer
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
AAAI
1998
14 years 10 months ago
1998
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
IJDAR
2010
14 years 8 months ago
2010
Inthispaper,weproposeadescriptorcombination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor. This ...
ESANN
2008
14 years 11 months ago
2008
