Speaker: John Hillas
Affiliation: Department of Economics, UoA
Title: Backward Induction in Games with Imperfect Recall (with D. Kvasov)
Date: Wednesday, 13 October 2010
Time: 4:00 pm
Location: 301-242 [Science Centre, Symonds Street]


The standard solution concepts motivated by the idea of backward induction, subgame perfect equilibrium, extensive form perfect equilibrium, sequential equilibrium, and quasi-perfect equilibrium were explicitly defined only for games with perfect recall.  In games with imperfect recall a literal application of the same definitions is clearly inappropriate.  We give definitions that coincide with the standard definitions in games with perfect recall and define sensible solutions in games without perfect recall.

The basic idea is to look, at subsets of each player’s information sets, at the pure strategies that make that those subsets reachable and to define a system of beliefs as associating to that strategy and that subset a distribution over the other players’ strategies.  We define the relevant solution concepts and show (conjecture) that the inclusions and the relation to proper equilibrium of the associated normal that were true for games with perfect recall remain true.

Very much work in progress.

The Centre for Mathematical Social Science has been officially established as a University of Auckland departmental centre in the Department of Mathematics. It supersedes the informal Mathematical Social Science group. We look forward to the future under this more formal arrangement.

Some information from the formal document setting up the centre:

The CMSS will provide a focus for academic exchanges between social scientists working with mathematical or computational methodologies, and researchers from pure and applied mathematical disciplines who are investigating problems with relevance to social science. It will
also facilitate cross-disciplinary supervision of research students and the teaching of inter-disciplinary courses. Students of mathematical or computational disciplines will discover new areas of application; and social scientists can learn about mathematical techniques that may be useful to their own research.

Since 2005, a group from the Departments of Mathematics, Economics, Computer Science, Statistics, and Engineering Science has run a lively seminar series on mathematical social science, hosted a range of distinguished academic visitors and co-organised several Workshops.
Establishment of the CMSS recognises the growing contribution of this group to the intellectual life of the University. More importantly, we intend that the Centre will contribute to the development of the group’s inter-disciplinary research agenda and expand the scope of its
activities, especially in the area of inter-disciplinary teaching. Faculty from the Departments of Philosophy and Finance are also amongst the founding members of the Centre, and we encourage even broader participation.

CMSS Advisory Board:

Prof. James Sneyd (HOD, Mathematics, Auckland) – CHAIR
Prof. Walter Bossert (Economics, Montreal)
Prof. Steven Brams (Political Science, NYU)
Prof. Andy McLennan (Economics, UQ)
Prof. Hervé Moulin (Economics, Rice)
Prof. Dr Jörg Rothe (Mathematics/Computer Science, Dusseldorf)
Prof. Toby Walsh (Computer Science, UNSW)
Prof. Bill Zwicker (Mathematics, Union College)

Speaker: Reyhaneh Reyhani
Affiliation: Computer Science Department, The University of Auckland
Title: A general model for effects of polls on voters’ behaviour
Date: Thursday, 4 Mar 2010
Time: 3:00 pm
Location: Room 401

The influence of pre-election polls on the result of an election is a problem that many authors have discussed. In this talk, we investigate this problem with a general model for m candidates under the plurality rule. Voters cannot be completely sure about the result of polls because of coverage bias or response bias. Therefore, we consider a general distribution of uncertainty in each poll for voters. We discuss the best strategy of voters according to the information that polls give them and how the sequence of polls leads voters to a unique equilibrium. We deduce a Duvergerian equilibrium in the limit in some cases. This is joint work in progress with Javad Khazaei and Mark Wilson.

Modelling Health Care: Combining real-world data in an “expert system” to test policy scenarios

Peter Davis, Director, COMPASS

There is increasing interest in the application of computational techniques in the social sciences, particularly in the area of modelling social processes. We present preliminary work in building a micro-simulation model of the system of decision-making in health care in the community whereby people experience illness and go to the doctor, who then responds. We combine data from different sources to give this model a solid base in the “real world” and we test it against external data. Policy scenarios are foreshadowed. There are major opportunities for collaborative work across disciplinary boundaries.

Note: COMPASS (www.compass.auckland.ac.nz) is a research group at UoA that uses quantitative, computational techniques in social sciences. The main purpose of this talk is to explore collaborative possibilities between the two groups.