Information Transformers and the
Concept of Informativeness
Dr. Peter Golubtsov
Moscow State University
We consider a uniform class of information transformers as a family
of morphisms of a category that satisfies a certain set of axioms.
The talk defines basic concepts for information transformers and studies
their main properties in terms of categories of information transformers.
In particular it generalizes the Bayesian approach to decision-making problems.
It also introduces two different approaches to comparison of informativeness
of information transformers and investigates their interrelations.
This topic incorporates a unified algebraic approach to statistics, fuzzy
decision making, etc., in a variety of applied problems. Several
examples of concrete categories of information transformers are presented.
Thursday, 10 February 2000
4:10 p.m. in Math 109
Coffee/treats at 3:30 p.m. Math 104 (lounge)
Spring 2000 Colloquium Schedule | Mathematical Sciences home | The University of Montana home