Abstract
This paper introduces a novel framework for designing multi-agent systems, called “Distributed Agent Evolution with Dynamic Adaptation to Local Unexpected Scenarios” (DAEDALUS). Traditional approaches to designing multi-agent systems are offline (in simulation), and assume the presence of a global observer. In the online (real world), there may be no global observer, performance feedback may be delayed or perturbed by noise, agents may only interact with their local neighbors, and only a subset of agents may experience any form of performance feedback. Under these circumstances, it is much more difficult to design multi-agent systems. DAEDALUS is designed to address these issues, by mimicking more closely the actual dynamics of populations of agents moving and interacting in a task environment. We use two case studies to illustrate the feasibility of this approach.
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© 2006 Springer-Verlag Berlin Heidelberg
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Hettiarachchi, S., Spears, W.M., Green, D., Kerr, W. (2006). Distributed Agent Evolution with Dynamic Adaptation to Local Unexpected Scenarios. In: Hinchey, M.G., Rago, P., Rash, J.L., Rouff, C.A., Sterritt, R., Truszkowski, W. (eds) Innovative Concepts for Autonomic and Agent-Based Systems. WRAC 2005. Lecture Notes in Computer Science(), vol 3825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11964995_22
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DOI: https://doi.org/10.1007/11964995_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69265-2
Online ISBN: 978-3-540-69266-9
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