Special Sessions

Special sessions will be open to all participants.

*Title of the session:

Interval Uncertainty

• List of organizers with contact details and short biographical details:

Martine Ceberio
Department of Computer Science
University of Texas at El Paso
El Paso, Texas 79968, USA
[email protected]
http://martineceberio.fr/

Dr. Ceberio is active both in fuzzy and interval computation
community, she is Past President of North American Fuzzy
Information Processing Society (NAFIPS), and also Editor-in-Chief
of Reliable Computing, the main journal of interval computations
community.

Vladik Kreinovich
Department of Computer Science
University of Texas at El Paso
El Paso, Texas 79968, USA
[email protected]
http://www.cs.utep.edu/vladik

Vladik Kreinovich is Vice-President of International Fuzzy Systems
Association (IFSA) and of the European Society for Fuzzy Logic and
Technology (EUSFLAT), Fellow of IFSA. He is also active in interval
community, he is a maintainer of the interval computations website
http://www.cs.utep.edu/interval-comp

• Description of the session, why the topic needs specific
attention and how it relates to soft computing

Interval uncertainty is closely related to fuzzy techniques:
indeed, if we want to know how the fuzzy uncertainty of the inputs
propagates through the data processing algorithm, then the usual
Zadeh's extension principle is equivalent to processing alpha-cuts
(intervals) for each level alpha.

This relation between intervals and fuzzy computations is well
known, but often, fuzzy researchers are unaware of the latest most
efficient interval techniques and thus use outdated less efficient
methods. One of the objectives of the proposed session is to help
fuzzy community by explaining the latest interval techniques and to
help interval community to better understand the related interval
computation problems.

Yet another relation between interval and fuzzy techniques is that
the traditional fuzzy techniques implicitly assume that experts can
describe their degree of certainty in different statements by an
exact number. In reality, it is more reasonable to expect experts
to provide only a range (interval) of possible values -- leading to
interval-valued fuzzy techniques that, in effect, combine both
types of uncertainty.