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SFM
2007
Springer
14 years 2 months ago
Tackling Large State Spaces in Performance Modelling
Stochastic performance models provide a powerful way of capturing and analysing the behaviour of complex concurrent systems. Traditionally, performance measures for these models ar...
William J. Knottenbelt, Jeremy T. Bradley
NIPS
2008
13 years 9 months ago
Multi-resolution Exploration in Continuous Spaces
The essence of exploration is acting to try to decrease uncertainty. We propose a new methodology for representing uncertainty in continuous-state control problems. Our approach, ...
Ali Nouri, Michael L. Littman
JMLR
2006
105views more  JMLR 2006»
13 years 7 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen
CORR
2008
Springer
91views Education» more  CORR 2008»
13 years 8 months ago
Particle Filtering for Large Dimensional State Spaces with Multimodal Observation Likelihoods
We study efficient importance sampling techniques for particle filtering (PF) when either (a) the observation likelihood (OL) is frequently multimodal or heavy-tailed, or (b) the s...
Namrata Vaswani
IROS
2007
IEEE
157views Robotics» more  IROS 2007»
14 years 2 months ago
Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
— In this paper, we present an approach that applies the reinforcement learning principle to the problem of learning height control policies for aerial blimps. In contrast to pre...
Axel Rottmann, Christian Plagemann, Peter Hilgers,...