Bottleneck analysis for self-adaption in multi-agent societies

We describe an approach to achieve dynamic adaption of an artificial agent society to environmental changes. Such changes cause sub-optimalities in the agent society design, leading to overloaded or underloaded agents or agent groups in the society. Our approach provides a mechanism to reveal these sub-optimalities by integrating bottleneck analysis to structural self-adaption in a generic multi-agent framework which allows one to incorporate agents of any architecture