Heuristic Search And Information Visualization Methods For School Redistricting

12:00 noon, April 01, Tuesday, 2008, ST2, 430A

Speaker

Marie desJardins
Associate Professor
Computer Science and Electrical Engineering
University of Maryland, Baltimore County
http://www.cs.umbc.edu/~mariedj/

Abstract

In this talk, I will describe an application of AI search and information visualization techniques to the problem of school redistricting, in which students are assigned to home schools within a county or school district. This is a multicriteria optimization problem in which competing objectives must be considered, such as school capacity, busing costs, and socioeconomic distribution. Because of the complexity of the decision-making problem, tools are needed to help end users generate, evaluate, and compare alternative school assignment plans. A key goal of this research is to aid users in finding multiple qualitatively different redistricting plans that represent different tradeoffs in the decision space.

I will present several heuristic search methods that can be used to find a set of qualitatively different plans, and will give empirical results of these search methods on population data from the school district of Howard County, Maryland. The resulting plans are displayed using novel visualization methods that we have developed for summarizing and comparing alternative plans.

Short Bio

Dr. Marie desJardins is an associate professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County. Prior to joining the faculty in 2001, Dr. desJardins was a senior computer scientist at SRI International in Menlo Park, California. Her research is in artificial intelligence, focusing on the areas of machine learning, multi-agent systems, planning, interactive AI techniques, information management, reasoning with uncertainty, and decision theory. Dr. desJardins can be reached at mariedj@cs.umbc.edu.