Nadine Hilgert

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We consider a class of discrete-time stochastic control systems, with Borel state and action spaces, and possibly unbounded costs. The processes evolve according to the equation x t+1 = F (x t , a t , ξ t), t = 0, 1,. .. , where the ξ t are i.i.d. random vectors whose common distribution is unknown. Assuming observability of {ξ t }, we use the empirical(More)
This work proposes a framework using temporal data and domain knowledge in order to analyze complex agronomical features. The expertise is first formalized in an ontology, under the form of concepts and relationships between them, and then used in conjunction with raw data and mathematical models to design a software sensor. Next the software sensor outputs(More)
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