Evolution-based self-adaption as an expression for the autonomy degree in multi-agent societies

This work focuses on the development of a method to allow multi-agent systems (MAS) to configure themselves to any application scale and nature. We describe an evolutionary approach to achieve a dynamic adaption of an artificial agent society to environment changes which makes a former efficient society structure suboptimal. Due to the inherent autonomy property of agents this self-adapting mechanism turns out to be an instrument to restrict the autonomy. Therefore, this mechanism provides an internal representation of the degree of agent autonomy in a multi-agent system.