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research article

Diffusion strategies for adaptation and learning over networks: an examination of distributed strategies and network behavior

Sayed, Ali H.  
•
Tu, Sheng-Yuan
•
Chen, Jianshu
Show more
2013
IEEE Signal Processing Magazine

Nature provides splendid examples of real-time learning and adaptation behavior that emerges from highly localized interactions among agents of limited capabilities. For example, schools of fish are remarkably apt at configuring their topologies almost instantly in the face of danger [1]: when a predator arrives, the entire school opens up to let the predator through and then coalesces again into a moving body to continue its schooling behavior. Likewise, in bee swarms, only a small fraction of the agents (about 5%) are informed, and these informed agents are able to guide the entire swarm of bees to their new hive [2]. It is an extraordinary property of biological networks that sophisticated behavior is able to emerge from simple interactions among lower-level agents [3].

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Type
research article
DOI
10.1109/MSP.2012.2231991
Author(s)
Sayed, Ali H.  
Tu, Sheng-Yuan
Chen, Jianshu
Zhao, Xiaochuan
Towfic, Zaid J.
Date Issued

2013

Publisher

IEEE

Published in
IEEE Signal Processing Magazine
Volume

30

Issue

3

Start page

155

End page

171

Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
ASL  
Available on Infoscience
December 19, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/143333
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