272 search results - page 29 / 55 » Parallel Reinforcement Learning with Linear Function Approxi... |
ICML
2009
IEEE
14 years 2 months ago
2009
IEEE
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Publication
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
ML
2002
ACM
13 years 7 months ago
2002
ACM
TD() is a popular family of algorithms for approximate policy evaluation in large MDPs. TD() works by incrementally updating the value function after each observed transition. It h...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
GECCO
2009
Springer
14 years 2 months ago
2009
Springer
Tetris is a falling block game where the player’s objective is to arrange a sequence of different shaped tetrominoes smoothly in order to survive. In the intelligence games, ag...