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A Novel Interactive Slime Mould Algorithm-Based Platform for Generative Art and Optimization

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Culture and Computing (HCII 2025)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 15800))

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Abstract

This study offers a new platform using the Slime Mould Algorithm (SMA) to let people generate complex visual designs via interactive simulations. Designed with WebGL and Three.js, the platform replicates multi-agent chemotaxis motivated by the dynamic adaptability of slime mould Physarum polycephalum. Two fundamental processes underlie the platform: a tailored text generating weight system and a tailored image fitting weight system. These mechanisms let users adjust pixel weightings, therefore guiding particles to create emergent, complex designs. Providing both accessibility for non-technical users and great degrees of creative flexibility, the platform combines computer graphics, visual arts, and computational physics. The system lets the development of original, changing artworks by integrating real-time input with dynamic rendering.

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Author information

Authors and Affiliations

  1. China Architecture Design and Research Group, Beijing, China

    Wen Wen

  2. Beihang University, Beijing, China

    Yuyao Zhang

  3. Royal College of Art, London, SW7 2EU, UK

    Jiaxuan Xu

  4. Shanghai Jiao Tong University, Shanghai, 200240, China

    Shan Wang

  5. Yonsei University, Seoul, Korea

    Jianghuai Shao

Authors
  1. Wen Wen
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  2. Yuyao Zhang
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  3. Jiaxuan Xu
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  4. Shan Wang
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  5. Jianghuai Shao
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Corresponding author

Correspondence to Jianghuai Shao .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Matthias Rauterberg

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Wen, W., Zhang, Y., Xu, J., Wang, S., Shao, J. (2025). A Novel Interactive Slime Mould Algorithm-Based Platform for Generative Art and Optimization. In: Rauterberg, M. (eds) Culture and Computing. HCII 2025. Lecture Notes in Computer Science, vol 15800. Springer, Cham. https://doi.org/10.1007/978-3-031-93160-4_13

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  • DOI: https://doi.org/10.1007/978-3-031-93160-4_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-93159-8

  • Online ISBN: 978-3-031-93160-4

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