Evolutionary algorithm for a genetic robot's personality based on the Myers-Briggs Type Indicator

Citations

WEB OF SCIENCE

6
Citations

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10

초록

The genetic robot has many configurable genes that contribute to defining the robot's personality. The large number of genes allows for a highly complex system, however it becomes increasingly difficult and time-consuming to ensure reliability, variability and consistency for the robot's personality while manually initializing values for the individual genes. To overcome this difficulty, this paper proposes MBTI-EAGRP. It is a fully autonomic gene-generative algorithm for a genetic robot's personality in a mobile phone. After grasping the user preferences through MBTI assessment using the neural network algorithm, the evolutionary algorithm generates and evolves a gene pool that customizes the robot's genome so that it closely matches a simplified set of personality features preferred by the user. Finally, an evaluation procedure for individuals is carried out in a virtual environment using tailored perception scenarios and real MBTI measurements. (C) 2012 Elsevier B.V. All rights reserved.

키워드

Genetic robot; Artificial creature; Artificial chromosome; Robot genome; Robot personality; MBTI; Neural network; Evolutionary algorithm; Mobile phone
제목
Evolutionary algorithm for a genetic robot's personality based on the Myers-Briggs Type Indicator
저자
Lee, Kang-Hee; Choi, Younggeun; Stonier, Daniel J.
DOI
10.1016/j.robot.2012.01.007
발행일
2012-07
유형
Article
저널명
Robotics and Autonomous Systems
권
60
호
7
페이지
941 ~ 961