Debugging multi-agent systems, which are concurrent, distributed, and consist of complex components, is difficult, yet crucial. In earlier work we have proposed mechanisms whereby...
Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
This paper presents a generic meta-model of multi-agent systems based on organizational concepts such as groups, roles and structures. This model, called AALAADIN, defines a very ...
We present our experiences using the RoboCup soccerserver simulator and Biter, our own agent platform, for the teaching of a graduate multiagent systems' class. The RoboCup s...
This paper presents an improved version of a multiagent architecture aimed at providing solutions for monitoring the interaction between the atmosphere and the ocean. The ocean sur...