We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
We present an approximate inference approach to parameter estimation in a spatio-temporal stochastic process of the reaction-diffusion type. The continuous space limit of an infer...
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
Structured QBDs by Abstraction Daniel Klink, Anne Remke, Boudewijn R. Haverkort, Fellow, IEEE, and Joost-Pieter Katoen, Member, IEEE Computer Society —This paper studies quantita...
Daniel Klink, Anne Remke, Boudewijn R. Haverkort, ...
Early detection of process disturbances and prediction of malfunctions in process equipment improve the safety of the process, minimize the time and resources needed for maintenan...
Tiina Komulainen, Mauri Sourander, Sirkka-Liisa J&...