The project is to build a Bayesian network that models a domain and makes some inferences. Available tools such as REES, Hugin and JavaBayes can be used. The system can be built using knowledge acquisition from expert in the domain or by learning from data or both. Following are domains used in the past.

Admission to a Phd program.
Loan expert advisor
Basketball simulator
Handicappers (piking winners in horseracing)
Selfpreserving building

Choose your domain, model it and deonstrate query processing over your model by REES/JavaBayes/Hugin.

TA assignments: Given class schedules for quarter, the number of TA needed for each class, TA’s preferences and qualification, and instructors’ choice of preferred TA, schedule the TA’s in a way that maximize some measure of staisfaction. (Real data may be available)(Talk to Andre Deloach)

Class scheduling: The problem is to find a schedule for classes, classrooms, and teachers for a teaching seting (e.g., a high school, a computer science department). Measure of satisfaction can be to minimize the number of weighted constraints violated. Students can use the REES tool to model and run their algorithms.

Combinatorial auctions:

• R. Menke, R. Dechter, "An Implementation of the Combinatorial Auction Problem in ECLIPSE", An ICS Technical Report, July, 2000
• Combinatorial Auction Test Suite (CATS)