813 search results - page 13 / 163 » Ensemble Algorithms in Reinforcement Learning |
MCS
2005
Springer
14 years 26 days ago
2005
Springer
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
EWRL
2008
13 years 9 months ago
2008
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
ROBOCUP
2007
Springer
14 years 1 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
NIPS
1997
13 years 8 months ago
1997
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
KDD
2001
ACM
14 years 7 months ago
2001
ACM
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...