536 search results - page 35 / 108 » Residual Algorithms: Reinforcement Learning with Function Ap... |
AAAI
2006
13 years 9 months ago
2006
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
NIPS
1998
13 years 9 months ago
1998
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
NIPS
2003
13 years 9 months ago
2003
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
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...