University of Birmingham > Talks@bham > Lab Lunch > Convergence of Preference Functions

Convergence of Preference Functions

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Dan Ghica.

A preference function is a function which selects a subset of objects based on (partial) information. As information increases, different objects may be selected. We examine conditions under which the selection of objects converges to the choice that would be made if full information were available, making use of tools from domain theory. The work is motivated by previous research (by Ficici, Bucci, Popovici) on co-evolutionary algorithms in which an evolving population of agents interact with each other and, it is hoped, produce better and better quality behaviour. The formalisation of how quality can be measured in this context has introduced the concept of a convex preference function. We simplify and extend the scope of this previous work, examining the relationship between convexity and convergence properties.

This talk is part of the Lab Lunch series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


Talks@bham, University of Birmingham. Contact Us | Help and Documentation | Privacy and Publicity.
talks@bham is based on from the University of Cambridge.