  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.
