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Distributed Submodular Minimization And Motion Planning Over Discrete State Space
2019
IEEE Transactions on Control of Network Systems
We develop a framework for the distributed minimization of submodular functions. Submodular functions are a discrete analog of convex functions and are extensively used in large-scale combinatorial optimization problems. While there has been a significant interest in the distributed formulations of convex optimization problems, distributed minimization of submodular functions has received relatively little research attention. Our framework relies on an equivalent convex reformulation of a
doi:10.1109/tcns.2019.2933993
fatcat:wzuddski25ax5pve4d4f66pzuy