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AmoebotSim 2.0: A Visual Simulation Environment for the Amoebot Model with Reconfigurable Circuits and Joint Movements (Media Exposition)

Authors Matthias Artmann , Tobias Maurer, Andreas Padalkin , Daniel Warner , Christian Scheideler

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Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Distributed computing models
  • Theory of computation → Self-organization
Keywords
  • Programmable matter
  • amoebot model
  • reconfigurable circuits
  • joint movements
  • simulator

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Abstract

We present AmoebotSim 2.0, a simulation environment for the geometric amoebot model of programmable matter that supports the reconfigurable circuit and joint movement extensions of the model. In the geometric amoebot model, we consider systems of simple computational entities called amoebots in a regular triangular grid environment. We are interested in distributed algorithms that solve coordination and shape formation problems. The reconfigurable circuit and joint movement extensions of the model allow the amoebots to communicate over greater distances and perform more complex movements, overcoming some limitations of the original model. AmoebotSim 2.0 is an open-source simulation environment that supports these extensions and provides a rich graphical interface, flexible simulation features, an extensive API, and comprehensive documentation.

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Matthias Artmann, Tobias Maurer, Andreas Padalkin, Daniel Warner, and Christian Scheideler. AmoebotSim 2.0: A Visual Simulation Environment for the Amoebot Model with Reconfigurable Circuits and Joint Movements (Media Exposition). In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 81:1-81:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.SoCG.2025.81

Author Details

Matthias Artmann
  • Paderborn University, Germany
Tobias Maurer
  • Paderborn University, Germany
Andreas Padalkin
  • Paderborn University, Germany
Daniel Warner
  • Paderborn University, Germany
Christian Scheideler
  • Paderborn University, Germany

Funding

This work was supported by the DFG Project SCHE 1592/10-1.

Supplementary Materials

References

  1. Matthias Artmann, Tobias Maurer, Andreas Padalkin, Daniel Warner, and Christian Scheideler. AmoebotSim 2.0. Software, version 1.8.4., DFG-SCHE 1592/10-1, (visited on 2025-06-02). URL: https://github.com/martmannupb/AmoebotSim-2.0
    Software Heritage Logo archived version
    full metadata available at: https://doi.org/10.4230/artifacts.23289
  2. Matthias Artmann, Andreas Padalkin, and Christian Scheideler. On the shape containment problem within the amoebot model with reconfigurable circuits. CoRR, abs/2501.16892, 2025. URL: https://doi.org/10.48550/arXiv.2501.16892.
  3. Joshua J. Daymude, Robert Gmyr, and Kristian Hinnenthal. AmoebotSim: A Visual Simulator for the Amoebot Model of Programmable Matter. Available online at https://github.com/SOPSLab/AmoebotSim, 2021.
  4. Joshua J. Daymude, Andréa W. Richa, and Christian Scheideler. The canonical amoebot model: Algorithms and concurrency control. Distributed Computing, 36(2):159-192, 2023. URL: https://doi.org/10.1007/s00446-023-00443-3.
  5. Zahra Derakhshandeh, Shlomi Dolev, Robert Gmyr, Andréa W. Richa, Christian Scheideler, and Thim Strothmann. Brief Announcement: Amoebot - A New Model for Programmable Matter. In Proceedings of the 26th ACM Symposium on Parallelism in Algorithms and Architectures, pages 220-222, Prague, Czech Republic, 2014. ACM. URL: https://doi.org/10.1145/2612669.2612712.
  6. Michael Feldmann, Andreas Padalkin, Christian Scheideler, and Shlomi Dolev. Coordinating Amoebots via Reconfigurable Circuits. Journal of Computational Biology, 29(4):317-343, 2022. URL: https://doi.org/10.1089/cmb.2021.0363.
  7. Andreas Padalkin, Manish Kumar, and Christian Scheideler. Reconfiguration and Locomotion with Joint Movements in the Amoebot Model. In Arnaud Casteigts and Fabian Kuhn, editors, 3rd Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2024), volume 292 of Leibniz International Proceedings in Informatics (LIPIcs), pages 18:1-18:20, Dagstuhl, Germany, 2024. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/LIPIcs.SAND.2024.18.
  8. Andreas Padalkin and Christian Scheideler. Polylogarithmic Time Algorithms for Shortest Path Forests in Programmable Matter. In Ran Gelles, Dennis Olivetti, and Petr Kuznetsov, editors, 43rd ACM Symposium on Principles of Distributed Computing, PODC '24, pages 65-75, New York, NY, USA, 2024. ACM. URL: https://doi.org/10.1145/3662158.3662776.
  9. Andreas Padalkin, Christian Scheideler, and Daniel Warner. The Structural Power of Reconfigurable Circuits in the Amoebot Model. In Thomas E. Ouldridge and Shelley F. J. Wickham, editors, 28th International Conference on DNA Computing and Molecular Programming (DNA 28), volume 238 of Leibniz International Proceedings in Informatics (LIPIcs), pages 8:1-8:22, Dagstuhl, Germany, 2022. Schloss Dagstuhl - Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/LIPIcs.DNA.28.8.
  10. Tommaso Toffoli and Norman Margolus. Programmable Matter: Concepts and Realization. International Journal of High Speed Computing, 05(02):155-170, 1993. URL: https://doi.org/10.1142/S0129053393000086.
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