Consensus Problem

The consensus problem focuses on achieving agreement among distributed agents, each possessing partial information, to a common value or solution. Current research emphasizes developing efficient algorithms, such as gradient-based methods and proximal algorithms, for achieving consensus in various settings, including those with constraints, time delays, and data heterogeneity, often leveraging optimization frameworks and distributed computing architectures. This research is crucial for advancing distributed systems in diverse fields, from multi-robot coordination and sensor networks to large-scale machine learning and federated optimization, where efficient and robust consensus is essential for optimal performance. The development of provably private and resilient consensus algorithms is also a significant area of focus, addressing privacy and security concerns in distributed applications.