Swarm Behavior

Swarm behavior research focuses on understanding and engineering the collective actions of multiple autonomous agents, aiming to achieve complex tasks through decentralized coordination. Current research emphasizes developing efficient algorithms, such as variations of particle swarm optimization and reinforcement learning, to design and control swarm behaviors, often incorporating human-in-the-loop approaches for improved performance and adaptability to dynamic environments. This field is significant for its potential applications in robotics, defense, and other areas requiring coordinated multi-agent systems, as well as for its contributions to understanding emergent behavior in biological and artificial systems.