34 search results - page 1 / 7 » Action Elimination and Stopping Conditions for Reinforcement... |
ICML
2003
IEEE
14 years 11 months ago
2003
IEEE
We consider incorporating action elimination procedures in reinforcement learning algorithms. We suggest a framework that is based on learning an upper and a lower estimates of th...
ICML
2007
IEEE
14 years 11 months ago
2007
IEEE
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
ICML
2009
IEEE
14 years 11 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
ECAI
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. This paper proposes a novel approach to discover options in the form of conditionally terminating sequences, and shows how they can be integrated into reinforcement learn...
AIPS
2010
14 years 1 months ago
2010
Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become in...