51 search results - page 4 / 11 » Exponentiated Gradient Methods for Reinforcement Learning |
ECML
2004
Springer
14 years 1 months ago
2004
Springer
Reinforcement learning (RL) algorithms attempt to assign the credit for rewards to the actions that contributed to the reward. Thus far, credit assignment has been done in one of t...
ICANNGA
2007
Springer
14 years 1 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
CIS
2005
Springer
14 years 1 months ago
2005
Springer
Recently, actor-critic methods have drawn much interests in the area of reinforcement learning, and several algorithms have been studied along the line of the actor-critic strategy...
AAAI
2010
13 years 9 months ago
2010
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...
AAAI
2000
13 years 9 months ago
2000
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...