Decentralized Ranking Aggregation: Gossip Algorithms for Borda and Copeland Consensus

Researchers have developed gossip algorithms that enable decentralized networks to reach consensus on rankings using Borda and Copeland methods without central coordination. The approach allows autonomous agents to compute global ranking consensus through local interactions, with applications in peer-to-peer networks, IoT, and multi-agent systems.