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The Author’s Journey - Understanding and improving the authoring process of theory-driven socially intelligent agents

过程(计算) 计算机科学 人机交互 过程管理 知识管理 工程类 操作系统
作者
Manuel Guimarães,Joana Campos,Pedro A. Santos,João Dias,Rui Prada
出处
期刊:ACM transactions on interactive intelligent systems [Association for Computing Machinery]
标识
DOI:10.1145/3711672
摘要

State of the art agent-modelling tools support the creation of powerful Socially Intelligent Agents (SIAs) capable of engaging in social interactions with participants in various roles and environments. However, their deployment demands a laborious authoring task as it is necessary to manually define behaviour rules and create content for different interaction scenarios. While Socially Intelligent Agents (SIAs) research has centered on the user experience, we shift focus to the authors. To understand the challenges faced by authors who create these agents, we performed an innovative analysis of the authoring experience in modern agent modelling tools. One key finding is that, while SIA concepts are generally understandable, emotional-based concepts are not as easily comprehended or used by authors. We propose a hybrid solution approach that culminated in the development of Authoring Assisted FAtiMA-Toolkit. The augmented agent modeling tool incorporates a data-driven authoring assistant to boost author productivity while promoting transparency and authorial control. To evaluate the impact of this framework on the authoring experience, we conducted a user study. Results showed that authors using the Authoring-Assisted FAtiMA-Toolkit were on average able to create more SIA-related content in less time. Our findings suggest that data-augmented, theory-grounded agent modeling tools can support the development of affective social agents by reducing the authoring burden without sacrificing the framework’s clarity or the authors’ control over the content
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