A Simulation Environment for the Neuroevolution of Ant Colony Dynamics

Michael Crosscombe, Ilya Horiguchi, Norihiro Maruyama, Shigeto Dobata, Takashi Ikegami
6/19/2024
cs.MAcs.NEnlin.AO

No official code found. Best implementation: toohuman/AntDynamics-Gymnasium (3 stars, Apache-2.0, last commit 2025-04-20).

Abstract

We introduce a simulation environment to facilitate research into emergent collective behaviour, with a focus on replicating the dynamics of ant colonies. By leveraging real-world data, the environment simulates a target ant trail that a controllable agent must learn to replicate, using sensory data observed by the target ant. This work aims to contribute to the neuroevolution of models for collective behaviour, focusing on evolving neural architectures that encode domain-specific behaviours in the network topology. By evolving models that can be modified and studied in a controlled environment, we can uncover the necessary conditions required for collective behaviours to emerge. We hope this environment will be useful to those studying the role of interactions in emergent behaviour within collective systems.

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Code Implementations(1)

toohuman/AntDynamics-GymnasiumCommunity100%
Apache-2.0

A Gymnasium domain for the learning of ant dynamics based on real ant colony data.

31Python, Jupyter NotebookJun 10, 20241 years agoApache-2.0

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Cite this paper

@article{crosscombe2024simulation,
  title  = {A Simulation Environment for the Neuroevolution of Ant Colony Dynamics},
  author = {Michael Crosscombe and Ilya Horiguchi and Norihiro Maruyama and Shigeto Dobata and Takashi Ikegami},
  year   = {2024},
  eprint = {2406.13147},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.13147v3}
}

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