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Fuzzy Interval Inference Utilizing the Checklist Paradigm and BK-Relational Products

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Applications of Interval Computations

Part of the book series: Applied Optimization ((APOP,volume 3))

Abstract

Many-valued logic based interval reasoning plays an increasingly important role in fuzzy and other many-valued extensions of two-valued (crisp) logic. It is often overlooked that many-valued logic (MVL) reasoning has a richer inference rule base than the crisp (i.e. classical two-valued) logic. Indeed some rules that are not possible in the crisp logic (which is point-based) do come to existence when we accept intervals as the basic elements of the semantic space ([0, 1] or a more general lattice) into which the logic expressions are valuated [11, 8, 37].

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Authors and Affiliations

  1. Department of Computer Science, Florida State University, Tallahassee, Florida, 32306-4019, USA

    L. J. Kohout & W. Bandler

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  1. L. J. Kohout
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  2. W. Bandler
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Editors and Affiliations

  1. University of Southwestern Louisiana, USA

    R. Baker Kearfott

  2. University of Texas at El Paso, USA

    Vladik Kreinovich

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© 1996 Kluwer Academic Publishers

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Kohout, L.J., Bandler, W. (1996). Fuzzy Interval Inference Utilizing the Checklist Paradigm and BK-Relational Products. In: Kearfott, R.B., Kreinovich, V. (eds) Applications of Interval Computations. Applied Optimization, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3440-8_12

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  • DOI: https://doi.org/10.1007/978-1-4613-3440-8_12

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