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
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;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891689