Deterministic and Probabilistic Implementation of Context

This paper addresses the problem of implementing an abstract context model. First, the abstract context model is represented by a network of situations. Two different implementations for the situation model are then proposed: a deterministic one based on Petri nets and a probabilistic one based on Hidden Markov Models. Both implementations are illustrated and applied to real-world problems.

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Computer Science [cs] Ubiquitous Computing Computer Science [cs] Modeling and Simulation

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Brdiczka06a.pdf (355 Ko)

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Dominique Vaufreydaz : Connect in order to contact the contributor

https://hal.inria.fr/inria-00326530

Submitted on : Friday, October 3, 2008-12:45:48 PM

Last modification on : Friday, February 25, 2022-3:07:40 AM

Long-term archiving on: Thursday, June 3, 2010-9:28:12 PM

Dates and versions

inria-00326530 , version 1 (03-10-2008)

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HAL Id : inria-00326530 , version 1

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Oliver Brdiczka, Patrick Reignier, James L. Crowley, Dominique Vaufreydaz, Jérôme Maisonnasse. Deterministic and Probabilistic Implementation of Context. IEEE International Conference on Pervasive Computing and Communications Workshops, Mar 2006, Pisa, Italy. 5 p. ⟨inria-00326530⟩

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