Tracking the Red Queen effect by estimating features of competitive co-evolutionary fitness landscapes

Open-ended evolution is considered to be caused by several factors, one of which would be co-evolution. Competitive co-evolution can give rise to the “Red Queen effect”, where the fitness landscape of each population is continuously changed by the competing population. Therefore, if such continuous changes are captured, co-evolutionary progress would be measured. In this paper, we estimate features of competitive co-evolutionary fitness landscapes on a predator-prey problem in computer simulations and investigate the Red Queen effect on the fitness landscape. Two types of method were proposed to estimate features, ruggedness and neutrality. One was calculated based on accumulated data so far at each generation, and the other was based on accumulated data during a certain period. The results suggest to us that our method can track the progress of fitness landscapes on competitive co-evolutionary robotics.