A Design Space for Intelligent Agents in Mixed-Initiative Visual Analytics

TL;DR

This paper introduces a comprehensive design space for intelligent agents in mixed-initiative visual analytics, providing a structured framework to guide the development and understanding of such systems based on a systematic review.

Contribution

It presents a novel six-dimensional design space for intelligent agents in mixed-initiative VA systems, derived from a systematic review of 90 systems and 207 agents.

Findings

Identified six key dimensions of intelligent agent design.

Provided a framework for situating and designing agents in VA systems.

Outlined future research directions in the field.

Abstract

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.