• DocumentCode
    226733
  • Title

    An interactive evolutionary computation framework controlled via EEG signals

  • Author

    Shen Ren ; Jiangjun Tang ; Barlow, Michael ; Abbass, Hussein A.

  • Author_Institution
    Sch. of Eng. & Inf. Technol., UNSW Canberra, Canberra, ACT, Australia
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    2402
  • Lastpage
    2409
  • Abstract
    This paper presents an EEG-based interactive genetic algorithm framework, with the goal of leveraging EEG signals collected from a human expert involved in the evaluation of interactive genetic algorithm as inputs for genetic parameter control. We explain the framework of the system and our cognitive model constructed based on a 19 channel EEG system. An experiment has been performed to test the effectiveness of our framework and our cognitive model. Our work is the first attempt to combine brain-computer interaction with interactive evolutionary computation and parameter control.
  • Keywords
    cognition; electroencephalography; genetic algorithms; medical signal processing; EEG signals; EEG-based interactive genetic algorithm framework; brain-computer interaction; channel EEG system; cognitive model; genetic parameter control; interactive evolutionary computation framework; Brain modeling; Electroencephalography; Feature extraction; Genetic algorithms; Genetics; Process control; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891689
  • Filename
    6891689