Abstract
Having shown that EMAS approaches are effective in solving selected benchmark and real-life problems, it would be interesting to take an insight into the exact features of the most important mechanism of EMAS, i.e. the distributed selection based on existence of non-renewable resource. Such experiments could help to understand it and tune the computation based on this knowledge. The problem is not trivial, because EMAS, similar to other metaheuristics, utilises many parameters imposing on the user the setting dozens of degrees of freedom.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Byrski, A., Kisiel-Dorohinicki, M. (2017). Tuning of EMAS Parameters. In: Evolutionary Multi-Agent Systems. Studies in Computational Intelligence, vol 680. Springer, Cham. https://doi.org/10.1007/978-3-319-51388-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-51388-1_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51387-4
Online ISBN: 978-3-319-51388-1
eBook Packages: EngineeringEngineering (R0)