131 search results - page 3 / 27 » Resolving Variations in Learning Spaces for Experiential Lea... |
CVPR
2006
IEEE
14 years 7 months ago
2006
IEEE
An activity consists of an actor performing a series of actions in a pre-defined temporal order. An action is an individual atomic unit of an activity. Different instances of the ...
AUSAI
1999
Springer
13 years 9 months ago
1999
Springer
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
CEC
2008
IEEE
13 years 12 months ago
2008
IEEE
— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
ROBOCUP
2007
Springer
13 years 11 months ago
2007
Springer
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
AR
2008
13 years 5 months ago
2008
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...