Multi-objective evolutionary generation process for specific personalities of artificial creature

Abstract

An artificial creature has its own genome in which each chromosome consists of many genes that contribute to defining its personality. The large number of genes allows a highly complex system. It becomes increasingly difficult and time-consuming to ensure reliability, variability and consistency for the artificial creature's personality, if gene values are manually assigned for the individual genome. To solve this problem, this paper proposes a multi-objective evolutionary generation process for artificial creatures' specific personalities (MOEGPP), where the dimension of the personality model is defined as that of optimization objectives. Key components of MOEGPP are as follows: i) the complement of (1 - k) dominance; ii) the pruning method considering objective deviation for all genomes;and iii) the inutation using biased normal distribution, to get a set of nondominated genomes with specific personalities according to the defined personality dimension. By proposed MOEGPP, nondominated genomes having specific personalities can be obtained and they are successfully tested by using an artificial creature, Rity, in the virtual 3D world created in a PC.