21 search results - page 4 / 5 » Bayesian reinforcement learning in continuous POMDPs with ga... |
NIPS
2008
13 years 7 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
PKDD
2009
Springer
14 years 27 days ago
2009
Springer
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
ICRA
2010
IEEE
13 years 4 months ago
2010
IEEE
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
NIPS
2008
13 years 7 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
JMLR
2010
13 years 1 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...