The objective of our research is first of all the development of a method
for learning the transition probabilities in (possibly hidden) Markov models
using imprecise probabilities, and next the application of this method to some
real-life problems. The learning model used will be the imprecise Dirichlet
model, an extension of the precise Dirichlet model to the theory of imprecise
probabilities. Possible applications are gene-sequence alignment and
pre-fetching of web pages.