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We present two distributed algorithms for the computation of a generalizedNash equilibrium in monotone games. The first algorithm follows from aforward-backward-forward operator splitting, while the second, which requiresthe pseudo-gradient mapping of the game to be cocoercive, follows from theforward-backward-half-forward operator splitting. Finally, we compare them withthe distributed, preconditioned, forward-backward algorithm via numericalexperiments.

Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking