A Simulation Environment for the Neuroevolution of Ant Colony Dynamics

Michael Crosscombe, Ilya Horiguchi, Norihiro Maruyama, Shigeto Dobata, Takashi Ikegami
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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.
蚁群动力学神经进化模拟环境
通过利用真实世界的数据,该环境模拟了目标蚂蚁的活动轨迹,可控代理必须利用目标蚂蚁观察到的感官数据,学习复制目标蚂蚁的活动轨迹。这项工作旨在为集体行为模型的神经进化做出贡献,重点是在网络拓扑中编码特定领域行为的神经架构的进化。通过进化可在受控环境中修改和研究的模型,我们可以发现集体行为出现所需的必要条件。我们希望这个环境能对研究集体系统中交互作用在萌发行为中的作用的人有所帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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