813 search results - page 33 / 163 » Ensemble Algorithms in Reinforcement Learning |
134
Voted
ATAL
2008
Springer
15 years 6 months ago
2008
Springer
Recent work in transfer learning has succeeded in making reinforcement learning algorithms more efficient by incorporating knowledge from previous tasks. However, such methods typ...
139
Voted
ICMLA
2008
15 years 5 months ago
2008
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
139
click to vote
ICMLC
2010
Springer
15 years 1 months ago
2010
Springer
: Bagging (Bootstrap Aggregating) has been proved to be a useful, effective and simple ensemble learning methodology. In generic bagging methods, all the classifiers which are trai...
131
Voted
ICML
2006
IEEE
16 years 4 months ago
2006
IEEE
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
160
click to vote
AGENTS
2001
Springer
15 years 8 months ago
2001
Springer
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...