Affiliations: [a] Department of Computer Science, University of Texas at El Paso, 500 W. University, El Paso, TX, USA | [b] Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM, USA, and Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand | [c] Department of Teacher Education, University of Texas at El Paso, 500 W. University, El Paso, TX, USA | [d] Department of Mathematics, Chiang Mai University, Chiang Mai, Thailand
Correspondence:
[*]
Corresponding author. Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, 500 W. University, El Paso, TX 79968, USA. Tel.: +1 915 747 6951; Fax: +1 915 747 5030; E-mail: [email protected].
Abstract: While many objects and processes in the real world are discrete, from the computational viewpoint, discrete objects and processes are much more difficult to handle than continuous ones. As a result, a continuous approximation is often a useful way to describe discrete objects and processes. We show that the need for such an approximation explains many features of fuzzy techniques, and we speculate on to which promising future directions of fuzzy research this need can lead us.
