A Simulation Environment for the Neuroevolution of Ant Colony Dynamics
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929550958526464 |
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| author | Crosscombe, Michael Horiguchi, Ilya Maruyama, Norihiro Dobata, Shigeto Ikegami, Takashi |
| author_facet | Crosscombe, Michael Horiguchi, Ilya Maruyama, Norihiro Dobata, Shigeto Ikegami, Takashi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_13147 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Simulation Environment for the Neuroevolution of Ant Colony Dynamics Crosscombe, Michael Horiguchi, Ilya Maruyama, Norihiro Dobata, Shigeto Ikegami, Takashi Multiagent Systems Neural and Evolutionary Computing Adaptation and Self-Organizing Systems 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. |
| title | A Simulation Environment for the Neuroevolution of Ant Colony Dynamics |
| topic | Multiagent Systems Neural and Evolutionary Computing Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2406.13147 |