Paper Info
Title
Learning from House-Hunting Ants: Collective Decision-Making in Organic Computing Systems
Abstract
This paper proposes ant-inspired strategies for self-organized and decentralized collective decision-making in computing systems which employ reconfigurable units. The particular principles used for the design of these strategies are inspired by the house-hunting of the ant Temnothorax albipennis. The considered computing system consists of two types of units: so-called worker units that are able to execute jobs that come into the system, and scout units that are additionally responsible for the reconfiguration process of all units. The ant-inspired strategies are analyzed experimentally and are compared to a non-adaptive reference strategy. It is shown that the ant-inspired strategies lead to a collective decentralized decision process through which the units are able to find good configurations that lead to a high system throughput even in complex configuration spaces.
Year
DOI
Venue
2008
10.1007/978-3-540-87527-7_9
ANTS Conference
Field
DocType
Volume
Computer science,Artificial intelligence,Decision process,Throughput,Organic computing,Temnothorax albipennis,Control reconfiguration,Computing systems,Group decision-making,Distributed computing
Conference
5217
ISSN
Citations 
PageRank 
0302-9743
5
0.79
References 
Authors
8
4
Name
Order
Citations
PageRank
Arne Brutschy125714.19
Alexander Scheidler218216.52
Daniel Merkle3383.68
Martin Middendorf41334161.45