Average Consensus

Average consensus algorithms enable a network of agents to collaboratively compute the average of their initial values, without relying on a central coordinator. Current research emphasizes developing robust algorithms resilient to adversarial agents or noisy communication channels, often employing iterative linear methods with distributed detection and recovery mechanisms or incorporating trust assessments. These advancements are crucial for reliable distributed decision-making in applications ranging from sensor networks and multi-agent systems to decentralized machine learning and control, where robustness and privacy are paramount.