Symbolic regression of generative network models

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@Article{Menezes:2014:SR,

• author = "Telmo Menezes and Camille Roth",
• title = "Symbolic regression of generative network models",
• journal = "Scientific Reports",
• year = "2014",
• volume = "4",
• number = "6284",
• month = "5 " # sep,
• keywords = "genetic algorithms, genetic programming, Machine learning. Applied mathematics, Scientific data, Software",
• ISSN = "2045-2322",
• URL = "http://www.telmomenezes.com/2014/09/using-evolutionary-computation-to-explain-network-growth/",
• URL = "http://www.nature.com/srep/2014/140905/srep06284/full/srep06284.html",
• DOI = "doi:10.1038/srep06284",
• size = "7 pages",
• abstract = "Networks are a powerful abstraction with applicability to a variety of scientific fields. Models explaining their morphology and growth processes permit a wide range of phenomena to be more systematically analysed and understood. At the same time, creating such models is often challenging and requires insights that may be counter-intuitive. Yet there currently exists no general method to arrive at better models. We have developed an approach to automatically detect realistic decentralised network growth models from empirical data, employing a machine learning technique inspired by natural selection and defining a unified formalism to describe such models as computer programs. As the proposed method is completely general and does not assume any pre-existing models, it can be applied out of the box to any given network. To validate our approach empirically, we systematically rediscover pre-defined growth laws underlying several canonical network generation models and credible laws for diverse real-world networks. We were able to find programs that are simple enough to lead to an actual understanding of the mechanisms proposed, namely for a simple brain and a social network.",
• notes = "Broken Oct 2021 https://groups.yahoo.com/neo/groups/genetic_programming/conversations/messages/6512 open source tool that implements the methodology describe in the paper: https://github.com/telmomenezes/synthetic",

}

Genetic Programming entries for Telmo Menezes Camille Roth

Citations