Mixed-initiative visual analytics (VA) systems, where human and artificial intelligence (AI) agents collaborate as equal partners during analysis, represented a paradigm shift in human-computer interaction. With recent advances in AI, these systems have seen an increase in sophisticated software agents that have improved task planning, reasoning, and completion capabilities. However, while existing work characterizes agent interplay and communication strategies, there is a limited understanding of the overarching design principles for intelligent agents. Through a systematic review of 90 systems (and 207 unique agents), we propose a design space of intelligent agents comprising six dimensions that collectively characterize an agent's perception, environmental understanding, action capability, and communication strategies. We contribute a novel framework for researchers and designers to explore various design choices for new systems and to situate a system in the current landscape. We conclude with future research opportunities for intelligent agents in mixed-initiative VA systems.

翻译：混合主动式可视化分析系统代表了人机交互领域的范式转变，其中人类与人工智能体在分析过程中作为平等伙伴进行协作。随着人工智能的最新进展，这些系统中涌现出越来越多具备更强任务规划、推理与完成能力的复杂软件智能体。然而，尽管现有研究描述了智能体的交互机制与通信策略，对于智能体的总体设计原则仍缺乏系统性认知。通过对90个系统（含207个独立智能体）的系统性综述，我们提出了一个包含六个维度的智能体设计空间，这些维度共同刻画了智能体的感知能力、环境理解、行动能力与通信策略。我们为研究者和设计者贡献了一个新颖的框架，可用于探索新系统的多样化设计选择，并将现有系统定位在当前研究版图中。最后，我们展望了混合主动式可视化分析系统中智能体未来的研究方向。