Can spiking networks control robot swarms?
Spiking Neural Networks as a Controller for Emergent Swarm Agents
October 22, 2024
https://arxiv.org/pdf/2410.16175This research investigates using spiking neural networks (SNNs) to control swarms of simple robots with limited sensing capabilities. The goal is to achieve complex emergent behavior (like milling in a circle) by optimizing the SNN's structure and parameters through an evolutionary algorithm.
While not directly using LLMs, the paper's focus on evolving communication and behavior in resource-constrained agents using minimal sensing directly applies to LLM-based multi-agent system development. It highlights the potential for using similar evolutionary approaches to develop sophisticated multi-agent interactions without relying on extensive pre-defined rules or complex individual agent capabilities.