%0 Conference Paper %B Artificial Life Conference Proceedings %D 2021 %T Diversity control in evolution of movement %A Komosinski, Maciej %A Miazga, Konrad %X In this work we investigate how various techniques of diversity control employed during evolution of 3D agents influence the velocity they achieve, and how these techniques influence the diversity of behaviors across multiple independent evolutionary runs. Three evolutionary settings are compared: a standard generational evolutionary process where fitness is velocity, a niching technique, and pure novelty search. Two genetic encodings (lower and higher level) and two environments (land and water) are used in experiments. To diversify behaviors, seven properties of movement introduced earlier are calculated for each individual during evolution. Best individuals obtained from evolution in each setting are compared both in terms of their fitness and the similarity of their movement patterns. %B Artificial Life Conference Proceedings %I MIT Press %G eng %R 10.1162/isal_a_00456