23 search results - page 4 / 5 » Combining Stochastic Task Models with Reinforcement Learning... |
NN
2006
Springer
13 years 6 months ago
2006
Springer
Previous studies have shown that non-human primates can generate highly stochastic choice behaviour, especially when this is required during a competitive interaction with another...
JMLR
2010
13 years 25 days ago
2010
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
ATAL
2005
Springer
13 years 11 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
ICRA
2003
IEEE
13 years 11 months ago
2003
IEEE
Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumptio...
CVPR
2010
IEEE
12 years 3 months ago
2010
IEEE
Robust tracking of abrupt motion is a challenging task
in computer vision due to the large motion uncertainty. In
this paper, we propose a stochastic approximation Monte
Carlo (...