An interactive evolutionary computation framework controlled via EEG signals
Shen Ren, Jiangjun Tang, Michael Barlow, Hussein A. Abbass · 2014
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.