On the synergy of network science and artificial intelligence

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Abstract

Traditionally science is done using the reductionism paradigm. Artificial intelligence does not make an exception and it follows the same strategy. At the same time, network science tries to study complex systems as a whole. This Ph.D. research takes an alternative approach to the reductionism strategy, and tries to advance both fields, i.e. artificial intelligence and network science, by searching for the synergy between them, while not ignoring any other source of inspiration, e.g. neuroscience.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI 2016)
Place of PublicationPalo Alto
PublisherAAAI Press
ISBN (Print)978-1-57735-770-4
Publication statusPublished - 2016
Event25th International Joint Conference on Artificial Intelligence (IJCAI-16), July 9-15, 2016, New York, NY, USA - New York, NY, United States
Duration: 9 Jul 201615 Jul 2016
http://ijcai-16.org

Conference

Conference25th International Joint Conference on Artificial Intelligence (IJCAI-16), July 9-15, 2016, New York, NY, USA
Abbreviated titleIJCAI-16
CountryUnited States
CityNew York, NY
Period9/07/1615/07/16
Internet address

Keywords

  • artificial intelligence
  • machine learning
  • deep learning
  • complex networks
  • network science

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