A new, formal, role-based, framework for modeling and analyzing both real world and artificial organizations is introduced. It exploits static and dynamic properties of the organiz...
Egon L. van den Broek, Catholijn M. Jonker, Alexei...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
We describe a system that successfully transfers value function knowledge across multiple subdomains of realtime strategy games in the context of multiagent reinforcement learning....
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
Abstract. This paper proposes a new model of communication in multiagent systems according to which the semantics of communication depends on their pragmatics. Since these pragmati...
Michael Rovatsos, Matthias Nickles, Gerhard Wei&sz...