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Visualization of dynamic structure in flocking behavior

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Abstract

The flock structures produced by individuals, e.g., animals, self-organize and change their complexity over time. Although flock structures are often characterized by the spatial alignment of each element, this study focuses on their dynamic and hierarchical nature, temporal variations, and meta-structures. In hierarchical systems, sometimes, the upper structure is unchanged, whereas the lower components change constantly over time. Current clustering methods aim to capture the static and mono-layer features of complex patterning. To detect and track dynamic and hierarchical objects, a new clustering technique is required. Hence, in this study, we improve the generative topographic mapping (GTM) method to visualize such dynamic hierarchical structures as they continuously change over time. Using examples from our recent studies on the large-scale Boids model, we confirm that the newly developed method can capture the complex flocking objects as well as track the merging and collapsing events of objects.

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Acknowledgements

This work was partially supported by MEXT under Post-K Computer Exploratory Challenge—Construction of Models for Interaction Among Multiple Socioeconomic Phenomena(hp170272). It was also partially supported by a Grant-in-Aid for Scientific Research (A) “Understanding and realization of swarm intelligence based on ethology and theory life sciences” (17H01249).

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Authors and Affiliations

  1. The Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan

    Daichi Saito, Norihiro Maruyama & Takashi Ikegami

  2. Division of Computer Science, The University of Aizu, Hukushima, Japan

    Yasuhiro Hashimoto

Authors
  1. Daichi Saito
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  2. Norihiro Maruyama
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  3. Yasuhiro Hashimoto
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  4. Takashi Ikegami
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Correspondence to Daichi Saito.

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This work was presented in part at the 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics (Okinawa, Japan, November 20–22, 2019).

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Saito, D., Maruyama, N., Hashimoto, Y. et al. Visualization of dynamic structure in flocking behavior. Artif Life Robotics 25, 544–551 (2020). https://doi.org/10.1007/s10015-020-00660-0

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