The article discusses the emergence of communication in swarms controlled by spiking neural networks (SNNs) during foraging tasks, similar to ant colony behavior. The study uses evolutionary algorithms to optimize SNNs, allowing agents to collaborate and navigate without predefined rules. Pheromone-based communication evolves naturally, improving swarm performance compared to non-communicating colonies. The research demonstrates how SNNs can self-organize and solve complex tasks, offering insights into swarm intelligence and bio-inspired computational models.
Access this article here: https://link.springer.com/article/10.1007/s11721-023-00231-6
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