Agent Topology

Agent topology research focuses on optimizing the connections and interactions within a network of agents to improve overall system performance. Current work explores using deep reinforcement learning and heuristic algorithms to design robust topologies, particularly for applications like power grid management and multi-agent systems. This research aims to enhance efficiency, resilience, and cooperation among agents, impacting fields such as distributed computing, IoT networks, and automated control systems by enabling more adaptable and reliable systems.