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@article{Lauri2013PlanningFM, title={Planning for multiple measurement channels in a continuous-state POMDP}, author={Mikko Lauri and Risto Ritala}, journal={Annals of Mathematics and Artificial Intelligence}, year={2013}, volume={67}, pages={283-317} }

- Published 2013 in Annals of Mathematics and Artificial Intelligence
DOI:10.1007/s10472-013-9361-y

Continuous-state partially observable Markov decision processes (POMDPs) are an intuitive choice of representation for many stochastic planning problems with a hidden state. We consider a continuous-state POMDPs with finite action and observation spaces, where the POMDP is parametrised by weighted sums of Gaussians, or Gaussian mixture models (GMMs). In… CONTINUE READING

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