536 search results - page 37 / 108 » Residual Algorithms: Reinforcement Learning with Function Ap... |
127
Voted
NECO
2010
15 years 1 months ago
2010
Most conventional Policy Gradient Reinforcement Learning (PGRL) algorithms neglect (or do not explicitly make use of) a term in the average reward gradient with respect to the pol...
113
Voted
JMLR
2010
14 years 9 months ago
2010
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
119
Voted
ATAL
2003
Springer
15 years 8 months ago
2003
Springer
Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...
114
Voted
ICML
2003
IEEE
16 years 3 months ago
2003
IEEE
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
109
Voted
ICML
2008
IEEE
16 years 3 months ago
2008
IEEE
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...