On decentralized computation of the leader's strategy in bi-level games

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We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

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On decentralized computation of the leader's strategy in bi-level games

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A learning-based approach to stochastic optimal control under reach-avoid constraint

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