Interactive evolution of human-robot communication in real world

Abstract

This paper describes how to implement interactive evolutionary computation (IEC) into a human-robot communication system. IEC is an evolutionary computation (EC) in which the fitness function is performed by human assessors. We used IEC to configure the human-robot communication system. We have already simulated IEC's application. In this paper, we implemented IEC into a real robot. Since this experiment leads considerable burdens on both the robot and experimental subjects, we propose the human-machine hybrid evaluation (HMHE) to increase the diversity within the genetic pool without increasing the number of interactions. We used a communication robot, WAMOEBA-3 (Waseda artificial mind on emotion base), which is appropriate for this experiment. In the experiment, human assessors interacted with WAMOEBA-3 in various ways. The fitness values increased gradually, and assessors felt the robot learnt the motions they desired. Therefore, it was confirmed that the IEC is most suitable as the communication learning system.