60 search results - page 1 / 12 » State-Space Inference and Learning with Gaussian Processes |
JMLR
2010
12 years 11 months ago
2010
NIPS
1998
13 years 6 months ago
1998
We present Monte-Carlo generalized EM equations for learning in nonlinear state space models. The dif
NIPS
2003
13 years 6 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
2003
IEEE
14 years 5 months ago
2003
IEEE
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
IROS
2009
IEEE
13 years 11 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...