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Monte Carlo Methods and Applications

Managing Editor: Sabelfeld, Karl K.

Editorial Board Member: Binder, Kurt / Bouleau, Nicolas / Chorin, Alexandre J. / Dimov, Ivan / Dubus, Alain / Egorov, Alexander D. / Ermakov, Sergei M. / Halton, John H. / Heinrich, Stefan / Kalos, Malvin H. / Lepingle, D. / Makarov, Roman / Mascagni, Michael / Mathe, Peter / Niederreiter, Harald / Platen, Eckhard / Sawford, Brian R. / Schmid, Wolfgang Ch. / Schoenmakers, John / Simonov, Nikolai A. / Sobol, Ilya M. / Spanier, Jerry / Talay, Denis

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CiteScore 2016: 0.70

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Source Normalized Impact per Paper (SNIP) 2016: 0.908

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1569-3961
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Volume 21, Issue 1 (Mar 2015)

Issues

Consensus in science

Peter Stallinga
  • Departamento de Engenharia Electrónica e Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
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/ Igor Khmelinskii
  • Departamento de Química e Farmácia, Faculdade de Ciências e Tecnologia, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
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Published Online: 2015-02-14 | DOI: https://doi.org/10.1515/mcma-2014-0008

Abstract

The biggest argument in some areas of science is the existence of a consensus. However, on top of it being a non-scientific argument, it is easy to show how a consensus naturally evolves in modern research environments. In this paper we demonstrate analytically and by cellular automata how a consensus is obtained. Important conclusions are that a consensus is not necessarily representing the truth and, once established, can never change anymore.

Keywords: Consensus analysis; cellular automata; Bayesian adjustment

MSC: 62P25; 62C05

About the article

Received: 2014-04-28

Accepted: 2014-12-23

Published Online: 2015-02-14

Published in Print: 2015-03-01


Citation Information: Monte Carlo Methods and Applications, ISSN (Online) 1569-3961, ISSN (Print) 0929-9629, DOI: https://doi.org/10.1515/mcma-2014-0008.

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© 2015 by De Gruyter. Copyright Clearance Center

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