27 search results - page 2 / 6 » Graph Kernels and Gaussian Processes for Relational Reinforc... |
PKDD
2010
Springer
13 years 2 months ago
2010
Springer
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
ICRA
2007
IEEE
13 years 11 months ago
2007
IEEE
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
PAMI
2006
13 years 4 months ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...