In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
We present two studies that evaluate the accuracy of human responses to an intelligent agent’s data classification questions. Prior work has shown that agents can elicit accurat...
We study the problem of distributed control of a large network of double-integrator agents to maintain a rigid formation. A few lead vehicles are given information on the desired t...
RADAR is a multiagent system with a mixed-initiative user interface designed to help office workers cope with email overload. RADAR agents observe experts to learn models of their...
Aaron Steinfeld, Andrew Faulring, Asim Smailagic, ...