Abstract
This paper presents in-formation flocking, a novel information visualization technique that extends the original information flocking concept with dynamic and data-driven visual formation behavior generation. This approach extends the emergent swarming properties of a decentralized multi-agent system in order to represent complex time-varying datasets through visually-recognizable formations and motion typologies. In-formation flocking is capable of representing volatile and inherently chaotic time-varying datasets while sustaining a comprehensible representation at a global level as well as revealing more detailed patterns in subsets of the data. This paper demonstrates the capabilities of in-formation flocking to historical stock market data.
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Vande Moere, A., Lau, A. (2007). In-Formation Flocking: An Approach to Data Visualization Using Multi-agent Formation Behavior. In: Randall, M., Abbass, H.A., Wiles, J. (eds) Progress in Artificial Life. ACAL 2007. Lecture Notes in Computer Science(), vol 4828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76931-6_26
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DOI: https://doi.org/10.1007/978-3-540-76931-6_26
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