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Evolutionary algorithm for a genetic robot's personality based on the Myers-Briggs Type Indicator
- Lee, Kang-Hee;
- Choi, Younggeun;
- Stonier, Daniel J.
WEB OF SCIENCE
6SCOPUS
10초록
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
- 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.
- 발행일
- 2012-07
- 유형
- Article
- 권
- 60
- 호
- 7
- 페이지
- 941 ~ 961
- 출판사
- ELSEVIER SCIENCE BV
- 발행국가
- 네덜란드
- 분량
- 21 페이지
- ISSN
- P 0921-8890