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» Gaussian Processes in Reinforcement Learning
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ISNN
2010
Springer
13 years 8 months ago
Particle Swarm Optimization Based Learning Method for Process Neural Networks
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
Kun Liu, Ying Tan, Xingui He
IROS
2008
IEEE
211views Robotics» more  IROS 2008»
14 years 4 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
IDEAL
2005
Springer
14 years 3 months ago
Neural Networks: A Replacement for Gaussian Processes?
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
Matthew Lilley, Marcus R. Frean
ICPR
2008
IEEE
14 years 4 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin
HIS
2008
13 years 11 months ago
The Hybrid Integration of Perceptual Symbol Systems and Interactive Reinforcement Learning
In order to produce robots which can interact more effectively with humans we propose that it is necessary for their cognitive processes to be grounded in the same perceptual elem...
Michael John Knowles, Stefan Wermter