Swarm Model

Swarm models aim to understand and predict the collective behavior of large groups of interacting agents, such as UAVs or biological organisms, focusing on emergent properties arising from decentralized local interactions. Current research emphasizes developing robust and scalable models, particularly those operating without centralized control or reliable communication, often drawing inspiration from biological systems and employing techniques like deep learning for system identification and novel algorithms for task allocation in dynamic environments. These advancements are crucial for improving the design and control of autonomous systems in diverse applications, ranging from environmental monitoring to search and rescue operations, and for gaining deeper insights into collective behavior in natural systems.