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Engineering Societies in the Agents World: First by Cristiano Castelfranchi (auth.), Andrea Omicini, Robert

By Cristiano Castelfranchi (auth.), Andrea Omicini, Robert Tolksdorf, Franco Zambonelli (eds.)

This publication constitutes the completely refereed post-proceedings of the 1st overseas Workshop on Engineering Societies within the brokers global, ESAW 2000, held in Berlin, Germany in August 2000. the ten revised complete papers offered have been rigorously reviewed and chosen for inclusion within the publication; they're geared up in topical sections on rising concerns in multi-agent structures engineering, coordination types and applied sciences for multi-agent structures, and methodologies and tools.

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Additional info for Engineering Societies in the Agents World: First International Workshop, ESAW 2000 Berlin, Germany, August 21, 2000 Revised Papers

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8. Ferber, J. Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Harlow, UK, Addison Wesley Longman, 1999. 9. , Deneubourg, J. , and Pasteels, J. M. Self-organized Shortcuts in the Argentine Ant. Naturwissenschaften, 76:579-581, 1989. 10. Huberman, B. A. and Glance, N. S. Evolutionary Games and Computer Simulations. Proceedings of the National Academy of Science USA, 90(August):7716-7718, 1993. 11. Kott, A. SEADy Storm. 2000. doc. 12. Moro, G. and Viroli, M. On Observing and Constraining Active Systems.

Thus AD movement becomes more random, and AD's are less likely to be found in the close vicinity of GT. 3. SEAD's travel with BMB's in Blue packages, which are attracted by GT. As AD's wander more, they are less likely to be near GT's, thus less likely to encounter SEAD's, and their survival increases. 4. Meanwhile (returning to the right-hand flap in Figure 2), the decreased population of BMB's leaves GT free to invade Blue territory. Lesson: Even simple rules interact in complex and unanticipated ways that designers must seek to understand through careful analysis.

Effective simulation science requires the development of similar guidelines, and the particular potential of agent-based modeling suggests that agent researchers should be in the forefront of developing this methodology. Acknowledgements Olga Gilmore and Murali Nandula of the ERIM CEC staff contributed significantly toward the experimentation reported in this paper. This work is supported in part by the DARPA JFACC program under contract F30602-99-C-0202 to ERIM CEC. The views and conclusions in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the US Government.

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