86 search results - page 3 / 18 » Estimation and Approximation Bounds for Gradient-Based Reinf... |
ATAL
2005
Springer
13 years 11 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
ATAL
2007
Springer
13 years 12 months ago
2007
Springer
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
ICML
2003
IEEE
14 years 6 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...
ICANN
2009
Springer
13 years 9 months ago
2009
Springer
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
JMLR
2010
13 years 17 days 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...