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Engineering - Computational Intelligence and Complexity | Evolutionary Intelligence - incl. option to publish open access (Editorial Board)

Evolutionary Intelligence

Evolutionary Intelligence

Editor-in-Chief: Larry Bull

ISSN: 1864-5909 (print version)
ISSN: 1864-5917 (electronic version)

Journal no. 12065


Larry Bull, Professor of Artificial Intelligence, Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Frenchay, Bristol, UK

Editorial Board:

  • Uwe Aickelin, University of Nottingham, U.K.
  • Randall Beer, Indiana University, U.S.A.
  • Andrea Bonarini, Politecnico di Milano, Italy
  • Lashon Booker, MITRE Corporation , U.S.A.
  • Martin V. Butz, Julius Maximilians Universität Würzburg, Germany
  • Jorge Casillas, Universidad de Granada, Spain
  • Dipankar Dasgupta, University of Memphis, U.S.A.
  • Dario Floreano, EPF Lausanne, Switzerland
  • David B. Fogel, Natural Selection Incorporated, U.S.A.
  • Stephanie Forrest, University of New Mexico, U.S.A.
  • Inman Harvey, University of Sussex, U.K.
  • Francisco Herrera, Universidad de Granada, Spain
  • Paulien Hogeweg, Utrecht University, The Netherlands
  • Phil Husbands, University of Sussex, U.K.
  • Hisao Ishibuchi, Osaka Prefecture University, Japan
  • Pier Luca Lanzi, Politecnico di Milano, Italy
  • Hod Lipson, Cornell University, U.S.A.
  • Xavier Llora, University of Illinois at Urbana-Champaign, U.S.A.
  • Risto Miikkulainen, University of Texas at Austin, U.S.A.
  • Melanie Mitchell, Portland State University, U.S.A.
  • Stefano Nolfi, Institute of Cognitive Sciences and Technologies, CNR, Italy
  • Robert E. Smith, University College London, U.K.
  • Dirk Thierens, Utrecht University, The Netherlands
  • Jon Timmis, University of York, U.K.
  • Lipo Wang, Nanyang Technological University, Singapore
  • Stewart W. Wilson, Prediction Dynamics, U.S.A.



For authors and editors

  • Aims and Scope

    Aims and Scope


    Evolutionary Intelligence is an international journal devoted to the publication and dissemination of theoretical and practical aspects of the use of population-based search for artificial intelligence. Techniques of interest include evolving rule-based systems, evolving artificial neural networks, evolving fuzzy systems, evolving Bayesian and statistical approaches, artificial immune systems, and hybrid systems which combine evolutionary computation with other A.I. techniques in general.

    The journal contains research papers, review articles, short notes and letters to the editor. Areas of interest include, but are not limited to, memory, vision, planning, knowledge representation and construction, robotics, neuroscience, language, development and learning, and all aspects of cognitive science. Papers describing applications in areas such as data mining, adaptive control, medical and bio-informatics, games and multi-media, agent-based computing and modelling, complex systems, and chemical and biological systems are also welcomed. The journal intends to capture and archive the advancement in the field of evolutionary intelligence in a timely manner and in one place.

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  • Open Choice - Your Way to Open Access
  • Instructions for Authors

    Instructions for Authors


  • Author Academy: Training for Authors
  • English Language Editing

    English Language Editing


  • Call for Paper - Evolutionary Robotics (...
  • Copyright information

    Copyright information


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