从计算情感模型到HRI

Jordi Vallverdú, D. Casacuberta, T. Nishida, Y. Ohmoto, Stuart Moran, S. Lázare
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引用次数: 6

摘要

在我们研究的前一阶段,我们开发了一种处理合成情绪的计算机模拟(称为“恐慌室”,或者更简单地称为“TPR”)。作者们正在开发进化机器的第一步,定义了复杂动作发展中涉及的关键元素(也就是说,从自下而上的方法创建一个物理直观的本体)。在TPR的初步结果取得成功后,作者认为有必要开发一种更复杂、具有更好可视化特征的新模拟(作者将其称为“TPR 2.0”)。在此之后,作者利用遗传算法(Game Of emotions, GOE)创建了一个情绪进化模拟,将特定情绪在社交领域的价值应用于日本Nishidalab的HRI真实机器人环境,重点研究了移情和接近学的概念。在那里,作者进行了一项实验,参与者包括来自两种不同母语文化的人,以及作为三种不同机器引入的一个机器人。最终获得的HRI数据在心理学、哲学、机器人科学和人类学等几个研究领域进行了分析。从计算情感模型到HRI
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Computational Emotional Models to HRI
During the previous stage of our research we developed a computer simulation (called ‘The Panic Room’ or, more simply, ‘TPR’) dealing with synthetic emotions. The authors were developing the first steps towards an evolutionary machine, defining the key elements involved in the development of complex actions (that is, creating a physical intuitive ontology, from a bottom-up approach). After the successful initial results of TPR, the authors considered that it would be necessary to develop a new simulation (which the authors will call “TPR 2.0.”), more complex and with better visualisation characteristics. After this, the authors created a simulation on emotions evolution with genetic algorithms (Game Of Emotions, GOE) which results on the value of specific emotions into social domains were applied to HRI real robotic environments at Nishidalab (Japan), focused into the notions of empathy and proxemics. There the authors performed an experiment that involved humans from two different native-speaking cultures and one robot introduced as three different machines. The final HRI obtained data was analyzed under several research field perspectives: psychology, philosophy, robotic sciences and anthropology. From Computational Emotional Models to HRI
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