Towards a Personality AI for Robots: Potential Colony Capacity of a Goal-Shaped Generative Personality Model When Used for Expressing Personalities

generative personality models goal-based personality models humanoid robots personality AI for robots robot personalities engineering

Journal

Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350

Informations de publication

Date de publication:
2022
Historique:
received: 22 06 2021
accepted: 30 03 2022
entrez: 31 5 2022
pubmed: 1 6 2022
medline: 1 6 2022
Statut: epublish

Résumé

Engineering robot personalities is a challenge of multiple folds. Every robot that interacts with humans is an individual physical presence that may require their own personality. Thus, robot personalities engineers face a problem that is the reverse of that of personality psychologists: robot personalities engineers need to make batches of identical robots into individual personalities, as oppose to formulating comprehensive yet parsimonious descriptions of individual personalities that already exist. The robot personality research so far has been fruitful in demonstrating the positive effects of robot personality but unfruitful in insights into how robot personalities can be engineered in significant quantities. To engineer robot personalities for mass-produced robots we need a generative personality model with a structure to encode a robot's individual characteristics as personality traits and generate behaviour with inter- and intra-individual differences that reflect those characteristics. We propose a generative personality model shaped by goals as part of a personality AI for robots towards which we have been working, and we conducted tests to investigate how many individual personalities the model can practically support when it is used for expressing personalities

Identifiants

pubmed: 35634263
doi: 10.3389/frobt.2022.728776
pii: 728776
pmc: PMC9131250
doi:

Types de publication

Journal Article

Langues

eng

Pagination

728776

Informations de copyright

Copyright © 2022 Luo, Ogawa, Peebles and Ishiguro.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Front Robot AI. 2022 Feb 21;9:717193
pubmed: 35265672
J Abnorm Soc Psychol. 1963 Jun;66:574-83
pubmed: 13938947
J Abnorm Psychol. 1946 Jul;41:258-90
pubmed: 20995551
J Pers. 1992 Jun;60(2):225-51
pubmed: 1635043
Am Psychol. 1993 Jan;48(1):26-34
pubmed: 8427480
J Pers Soc Psychol. 1985 Sep;49(3):710-21
pubmed: 4045699
Psychol Sci. 2019 Jun;30(6):893-906
pubmed: 31009583
J Pers Soc Psychol. 2002 May;82(5):804-18
pubmed: 12003479
J Pers Soc Psychol. 1990 Dec;59(6):1216-29
pubmed: 2283588

Auteurs

Liangyi Luo (L)

Intelligent Robotics Laboratory, Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.

Kohei Ogawa (K)

Intelligent System Laboratory, Graduate School of Engineering, Nagoya University, Nagoya, Japan.

Graham Peebles (G)

Intelligent Robotics Laboratory, Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.

Hiroshi Ishiguro (H)

Intelligent Robotics Laboratory, Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.

Classifications MeSH