Our demo presents an agent-based intrusion detection system designed for deployment on high-speed backbone networks. The major contribution of the system is the integration of sev...
We consider a class of networks where n agents need to send their traffic from a given source to a given destination over m identical, non-intersecting, and parallel links. For suc...
Opponent modeling is a skill in multi-agent systems (MAS) which attempts to create a model of the behavior of the opponent. This model can be used to predict the future actions of ...
Imitation-based learning is a general mechanism for rapid acquisition of new behaviors in autonomous agents and robots. In this paper, we propose a new approach to learning by imit...
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...