Analysis of Changes Occurring to Interactive Evolutionary Computation Users Through Continuous Task Execution

Abstract

Interactive evolutionary computation (IEC) is one type of evolutionary computation which includes a human user as an evaluation system. When a human as an evaluator repeats evaluation of an individual (solution candidate), he/she could be aware of his/her preference more deeply. Also, if we can reveal features of genotypes related to the awareness, it would be possible to produce better individuals including the features for him/her. In the paper we investigate if a person recognizes his/her preference well when he/she conducts an independent run for a given IEC task sequentially multiple times. We focus on mutual information of a pair of loci (positions on an individual) as the feature. The results show that most people can be aware of their preference well through sequential multiple runs and the feature corresponds to the awareness well.