<div class="csl-bib-body">
<div class="csl-entry">Dhanoa, V., Wolter, A., León, G. M., Schulz, H.-J., & Elmqvist, N. (2025). Agentic Visualization: Extracting Agent-Based Design Patterns From Visualization Systems. <i>IEEE Computer Graphics and Applications</i>, <i>45</i>(6), 89–100. https://doi.org/10.1109/MCG.2025.3607741</div>
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dc.identifier.issn
0272-1716
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/225028
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dc.description.abstract
Autonomous agents powered by large language models are transforming artificial intelligence (AI), creating an imperative for the visualization area. However, our field's focus on a human in the sensemaking loop raises critical questions about autonomy, delegation, and coordination for such agentic visualization that preserve human agency while amplifying analytical capabilities. This article addresses these questions by reinterpreting existing visualization systems with semiautomated or fully automatic AI components through an agentic lens. Based on this analysis, we extract a collection of design patterns for agentic visualization, including agentic roles, communication, and coordination. These patterns provide a foundation for future agentic visualization systems that effectively harness AI agents while maintaining human insight and control.
en
dc.language.iso
en
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dc.publisher
IEEE COMPUTER SOC
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dc.relation.ispartof
IEEE Computer Graphics and Applications
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dc.subject
agents
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dc.subject
visualization
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dc.subject
design patterns
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dc.title
Agentic Visualization: Extracting Agent-Based Design Patterns From Visualization Systems
