Submodular Optimization for Consensus Networks With Noise-Corrupted Leaders
Submodular Optimization for Consensus Networks With Noise-Corrupted Leaders is a scholarly work by Stacy Patterson, published in 2019 in ''IEEE Transactions on Automatic Control''. The main subjects of the publication include variance, selection (genetic algorithm), node, noise, state, multi-agent system, greedy algorithm, mathematical optimization, gene expression, biological function, submodular set function, set, mathematics, combinatorial optimization, computer science, and set function. The authors first show that this performance measure can be expressed as a submodular set function over the nodes in the network.