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Measures of Observables and Measures of Fuzziness

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Advances in Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 298))

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Abstract

The key aims of modern scientific work have generally been to find relationships between observed phenomena, construct mathematical formulas that describe these relationships, take measurements of the observables, and define axioms using terms that are as exact as possible. In many circumstances, the exactness of observed phenomena is limited – or can only be measured with less than perfect accuracy. However, another problem arises if the concepts of a scientific theory do not fit with the picture that scientists use to understand their observations and experimental results. How to deal with such situations is a question that has intrigued many scientists and philosophers. In the 20th century two scientific theories appeared that change scientist’s views from classical to non-classical and on what is measurable: quantum mechanics and fuzzy set theory. This paper focuses on these developments.

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Authors and Affiliations

  1. European Centre for Soft Computing, Edificio de Investigación, Calle Gonzalo Gutiérrez Quirós S/N, 33600, Mieres, Asturias, Spain

    Rudolf Seising

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  1. Rudolf Seising
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. Université Pierre et Marie Curie - Paris6, CNRS UMR 7606, DAPA, LIP6 8, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute, IONA College, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Seising, R. (2012). Measures of Observables and Measures of Fuzziness. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31715-6_7

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  • DOI: https://doi.org/10.1007/978-3-642-31715-6_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31714-9

  • Online ISBN: 978-3-642-31715-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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