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A genetic algorithm-based approach to mapping the diversity of networks sharing a given degree distribution and global clustering
conference contribution
posted on 2023-06-09, 03:55 authored by Peter Overbury, Istvan Kiss, Luc BerthouzeLuc BerthouzeThe structure of a network plays a key role in the outcome of dynamical processes operating on it. Two prevalent network descriptors are the degree distribution and the global clustering. However, when generating networks with a prescribed degree distribution and global clustering, it has been shown that changes in structural properties other than that controlled for are induced and these changes have been found to alter the outcome of spreading processes on the network. This therefore begs the question of our understanding of the potential diversity of networks sharing a given degree distribution and global clustering. As the space of all possible networks is too large to be systematically explored, a heuristic approach is needed. In our genetic algorithm-based approach, networks are encoded by their subgraph counts from a chosen family of subgraphs. Coverage of the space of possible networks is then maximised by focusing the search through optimising the diversity of counts by the Map-Elite algorithm. We provide preliminary evidence of our approach’s ability to sample from the space of possible networks more widely than some state of the art methods.
History
Publication status
- Published
File Version
- Accepted version
Journal
Complex Networks & Their Applications VPublisher
SpringerExternal DOI
Volume
693Page range
223-233Pages
11.0Event name
5th International Workshop on Complex Networks and their ApplicationsEvent location
MilanEvent type
conferenceEvent date
30th November - 2nd December 2016Book title
Complex networks & their applications V: proceedings of the 5th international workshop on complex networks and their applicationsISBN
9783319509006Series
Studies in computational intelligenceDepartment affiliated with
- Informatics Publications
Research groups affiliated with
- Centre for Computational Neuroscience and Robotics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Editors
Sabrina Gaito, Hocine Cherifi, Alessandra Sala, Walter QuattrociocchiLegacy Posted Date
2016-12-05First Open Access (FOA) Date
2016-12-05First Compliant Deposit (FCD) Date
2016-12-05Usage metrics
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