582 search results - page 9 / 117 » Gaussian Processes in Reinforcement Learning |
ESSMAC
2003
Springer
14 years 2 months ago
2003
Springer
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
ATAL
2009
Springer
14 years 4 months ago
2009
Springer
We consider the setting of multiple collaborative agents trying to complete a set of tasks as assigned by a centralized controller. We propose a scalable method called“Assignmen...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matr...
DSMML
2004
Springer
14 years 3 months ago
2004
Springer
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...