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迈向用于机器人的个性人工智能:目标形状生成个性模型用于表达个性时类人机器人的潜在群体能力及非语言行为。

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

作者信息

Luo Liangyi, Ogawa Kohei, Peebles Graham, Ishiguro Hiroshi

机构信息

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

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

出版信息

Front Robot AI. 2022 May 11;9:728776. doi: 10.3389/frobt.2022.728776. eCollection 2022.

Abstract

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 non-verbal behaviour on the heads of humanoid robots.

摘要

设计机器人个性是一项多方面的挑战。每一个与人类互动的机器人都是一个独立的物理实体,可能需要有自己的个性。因此,机器人个性工程师面临的问题与个性心理学家的问题相反:机器人个性工程师需要将一批相同的机器人塑造出各自的个性,而不是对已存在的个体个性进行全面而简洁的描述。到目前为止,机器人个性研究在证明机器人个性的积极影响方面成果丰硕,但在深入了解如何大规模设计机器人个性方面却毫无建树。为了给大规模生产的机器人设计个性,我们需要一个生成式个性模型,其结构能够将机器人的个体特征编码为个性特质,并生成反映这些特征的个体间和个体内有差异的行为。我们提出了一个由目标塑造的生成式个性模型,作为我们一直在研究的机器人个性人工智能的一部分,并且我们进行了测试,以调查当该模型用于在人形机器人头部表达个性的非语言行为时,它实际上能够支持多少种个体个性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e967/9131250/b08c28dcaa62/frobt-09-728776-g001.jpg

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