92 search results - page 12 / 19 » A General Convergence Method for Reinforcement Learning in t... |
JMLR
2010
13 years 1 months ago
2010
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
GECCO
2009
Springer
14 years 1 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...
ICML
2000
IEEE
14 years 7 months ago
2000
IEEE
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
JMLR
2010
13 years 5 months ago
2010
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
GECCO
2007
Springer
14 years 26 days ago
2007
Springer
Recent research into single–objective continuous Estimation– of–Distribution Algorithms (EDAs) has shown that when maximum–likelihood estimations are used for parametric d...