In this paper we introduce an object-oriented coordination language for multi-agents systems. The beliefs and reasoning capabilities ent are specified in terms of a corresponding ...
Frank S. de Boer, Cees Pierik, Rogier M. van Eijk,...
Emergent self-organization in multi-agent systems appears to contradict the second law of thermodynamics. This paradox has been explained in terms of a coupling between the macro ...
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Developing scalable coordination algorithms for multi-agent systems is a hard computational challenge. One useful approach, demonstrated by the Coverage Set Algorithm (CSA), explo...