A Simulation Environment for the Neuroevolution of Ant Colony Dynamics

TL;DR

This paper presents a simulation environment designed to facilitate neuroevolution research on ant colony dynamics, enabling the study of emergent collective behaviors through evolving neural models based on real-world ant trail data.

Contribution

The work introduces a novel simulation platform that allows for evolving neural architectures to replicate ant colony behaviors using real-world data.

Findings

Environment successfully simulates ant trail dynamics

Neural models can learn to replicate collective behaviors

Framework supports studying interaction effects in emergent systems

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.