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IROS
2008
IEEE
211views Robotics» more  IROS 2008»
14 years 2 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
EDUTAINMENT
2007
Springer
14 years 1 months ago
An Observational Study of Children Interacting with an Augmented Story Book
We present findings of an observational study investigating how young children interact with augmented reality story books. Children aged between 6 and 7 read and interacted with o...
Andreas Dünser, Eva Hornecker
KI
2008
Springer
13 years 7 months ago
Learning by Observing: Case-Based Decision Making in Complex Strategy Games
Abstract. There is a growing research interest in the design of competitive and adaptive Game AI for complex computer strategy games. In this paper, we present a novel approach for...
Darko Obradovic, Armin Stahl
CORR
2011
Springer
170views Education» more  CORR 2011»
13 years 2 months ago
Exact observability, square functions and spectral theory
Abstract. In the first part of this article we introduce the notion of a backwardforward conditioning (BFC) system that generalises the notion of zero-class admissibiliy introduce...
Bernhard Hermann Haak, El-Maati Ouhabaz
IJRR
2010
162views more  IJRR 2010»
13 years 6 months ago
Planning under Uncertainty for Robotic Tasks with Mixed Observability
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...