VTS-ID/8194

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URL: http://vts.uni-ulm.de/doc.asp?id=8194
URN: urn:nbn:de:bsz:289-vts-81945

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Titel Consistency in stochastic networks
Autor / Hrsg. Hasseln, Hermann von
Martignon, Laura
Dokumentart Report (Bericht)
Serie / Reihe

 Ulmer Informatik-Berichte
Institution Universität Ulm.  Fakultät für Ingenieurwissenschaften und Informatik
DDC-Sachgruppe Data processing & computer science (ddc:004)
Schlagwörter
(): Schlagwortschema		 Expert systems (Computer science) (LCSH)
Markov processes (LCSH)
Stochastic models (LCSH)
Stochastisches Modell (SWD)
Sprache englisch
Jahr der Erstellung 1992
Signatur QAA 5/A4.92,9
VTS-Veröffentlichung 07.09.2012
Statistik 113 Zugriffe seit 13.09.2012
Abstract Stochastic networks are given by graphs, whose vertices (nodes, neurons or spins) can take one out of a finite number of states at any given time. The way each vertex changes its state over time is determined by the edges connecting it with other vertices. The edges represent probabilistic dependencies. Updating is usually performed in a parallel or sequential way. Stochastic networks are used to model expert sytems; in this context confidence numbers are given as dependencies between vertices and the problem is to see, to what extent they are stochastically consistent. Given a graph and a set (or subset) of confidence numbers, we give a procedure that, starting from these confidence numbers, leads to local characteristics which are consistent with the graph.

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