Electrical Engineering and Computer Science

Electronic Commerce

Automating commerce operations promises substantial economic benefits, and presents many interesting challenges for artificial intelligence. For example, autonomous bidding agents can improve the efficiency of markets by lowering transaction costs and facilitating the identification of superior trades. Bidding effectively in any given domain requires high-quality modeling, planning and optimization, prediction, and strategic reasoning. Michigan’s research in electronic commerce emphasizes automated trading in computational markets, as well as incentive-centered design of markets and other commerce-related mechanisms. Fundamental research in multiagent learning, algorithmic game theory, and social computing mechanisms also contributes to this area.
Abernethy, Jacob
Baveja, Satinder Singh
Durfee, Edmund H
Wellman, Michael

Affiliated Faculty
Schoenebeck, Grant

Related Labs, Centers, and Groups
STIET Program