The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...
We describe a framework and equations used to model and predict the behavior of multi-agent systems (MASs) with learning agents. A difference equation is used for calculating the ...
This paper investigates the problem of policy learning in multiagent environments using the stochastic game framework, which we briefly overview. We introduce two properties as de...
Abstract. While high interactivity has been one of the main characteristics of oneon-one human tutoring, a great deal of controversy surrounds the issue of whether interactivity is...
Min Chi, Pamela W. Jordan, Kurt VanLehn, Diane J. ...
This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. It...