Development of user-adaptive value system of learning function using interactive EC

Yuki Suga, Shigeki Sugano, Yoshinori Ikuma, Tetsuya Ogata

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Our goal is to create a user-adaptive communication-robot. We are developing a system for evaluating human-robot interactions. Although such evaluation is indispensable for learning algorithms, users' preferences are too difficult to model because they are subjective. In this study, we used the interactive evolutionary computation (IEC) to configure the value system of a learning communicationrobot. The IEC is a genetic algorithm whose fitness function is performed by the user. In our experiment, we encoded the values of sensors (reward or punishment) into genes, and subjects interacted with the learning robot. Through the interaction, the subjects evaluated the robot by touching its sensors, and the robot learned appropriate combinations between input and output. Afterward, the subjects gave their scores to the experimenter, and the scores were regarded as the fitness values of the corresponding genes. These sequences were continued until the 4 generation, and then the subjects compared three of their best genes and two of the experimenter's. We found that the user-adaptive value system is suitable for the communication-robot.

Original languageEnglish
Title of host publicationIFAC Proceedings Volumes (IFAC-PapersOnline)
Edition1 PART 1
Publication statusPublished - 2008
Externally publishedYes
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul
Duration: 2008 Jul 62008 Jul 11


Other17th World Congress, International Federation of Automatic Control, IFAC



  • Intelligent robotics
  • Multi-modal interaction

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this