Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking
Barbara Franci, Mathias Staudigl, Sergio Grammatico
Abstract
We present two distributed algorithms for the computation of a generalized Nash equilibrium in monotone games. The first algorithm follows from a forward-backward-forward operator splitting, while the second, which requires the pseudo-gradient mapping of the game to be cocoercive, follows from the forward-backward-half-forward operator splitting. Finally, we compare them with the distributed, preconditioned, forward-backward algorithm via numerical experiments.
Topics & Concepts
Nash equilibriumMonotone polygonAlgorithmComputationComputer scienceOperator (biology)Distributed algorithmMathematicsMathematical optimizationApplied mathematicsDistributed computingChemistryBiochemistryGeneRepressorTranscription factorGeometryQuantum Information and CryptographyMathematical Biology Tumor GrowthMathematical and Theoretical Epidemiology and Ecology Models