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

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1 Author(s)
Gerber, C. ; German Res. Center for Artificial Intelligence, Saarbrucken, Germany

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

Published in:

Intelligent Control (ISIC), 1998. Held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Proceedings

Date of Conference:

14-17 Sep 1998