The visual analytics community has long aimed to understand users better and assist them in their analytic endeavors. As a result, numerous conceptual models of visual analytics aim to formalize common workflows, techniques, and goals leveraged by analysts. While many of the existing approaches are rich in detail, they each are specific to a particular aspect of the visual analytic process. Furthermore, with an ever-expanding array of novel artificial intelligence techniques and advances in visual analytic settings, existing conceptual models may not provide enough expressivity to bridge the two fields. In this work, we propose an agent-based conceptual model for the visual analytic process by drawing parallels from the artificial intelligence literature. We present three examples from the visual analytics literature as case studies and examine them in detail using our framework. Our simple yet robust framework unifies the visual analytic pipeline to enable researchers and practitioners to reason about scenarios that are becoming increasingly prominent in the field, namely mixed-initiative, guided, and collaborative analysis. Furthermore, it will allow us to characterize analysts, visual analytic settings, and guidance from the lenses of human agents, environments, and artificial agents, respectively.

翻译：视觉分析领域长期以来一直致力于更深入地理解用户并协助其完成分析任务。为此，众多视觉分析的概念模型试图对分析人员常用的工作流程、技术和目标进行形式化描述。尽管现有方法细节丰富，但它们各自仅聚焦于视觉分析过程的特定方面。此外，随着层出不穷的新型人工智能技术以及视觉分析场景的进步，现有概念模型可能无法提供足够的表达能力来桥接这两个领域。在本研究中，我们借鉴人工智能文献中的思路，提出了一种基于智能体的视觉分析过程概念模型。我们以视觉分析文献中的三个实例作为案例研究，并使用我们的框架对其进行详细分析。我们简单而稳健的框架统一了视觉分析流程，使研究人员和实践者能够对领域中日渐突出的场景——即混合主动、引导式和协作式分析——进行推理。此外，该框架还将使我们能够从人类智能体、环境和人工智能体的视角，分别对分析人员、视觉分析场景和引导过程进行刻画。