Abstract
Adaptive multiagent algorithms based upon the behaviour of social insects are powerful decentralised systems capable of solving complex problems. The intelligence of such a system lies not within a single agent but is a product of a network of simple interactions. Under the context of a mail collection environment different techniques are implemented and evaluated. The paper creates a number of strategies to tackle task allocation problems of this type based upon the principles of self-organisation and greedy search. The paper also investigates factors that may affect their performance.
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© 2004 Springer-Verlag Berlin Heidelberg
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Price, R., Tiňo, P. (2004). Evaluation of Adaptive Nature Inspired Task Allocation Against Alternate Decentralised Multiagent Strategies. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_99
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DOI: https://doi.org/10.1007/978-3-540-30217-9_99
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23092-2
Online ISBN: 978-3-540-30217-9
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