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Linear-Quadratic Dynamic Games as Receding-Horizon Variational Inequalities

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arxiv 2408.15703 v2 pith:AI25HFV4 submitted 2024-08-28 eess.SY cs.SYmath.OC

classification eess.SYcs.SYmath.OC
keywords nashreceding-horizonasymptoticcost-to-godynamicequilibriumequivalentgames
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We consider dynamic games with linear dynamics and quadratic objective functions. We observe that the unconstrained open-loop Nash equilibrium coincides with a linear quadratic regulator in an augmented space, thus deriving an explicit expression of the cost-to-go. With such cost-to-go as a terminal cost, we show asymptotic stability for the receding-horizon solution of the finite-horizon, constrained game. Furthermore, we show that the problem is equivalent to a non-symmetric variational inequality, which does not correspond to any Nash equilibrium problem. For unconstrained closed-loop Nash equilibria, we derive a receding-horizon controller that is equivalent to the infinite-horizon one and ensures asymptotic stability.

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Cited by 2 Pith papers

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  1. Learning under Opponent Unawareness in Linear-Quadratic Stochastic Games

    math.OC 2026-08 conditional novelty 7.0 of 10

    Radically uncoupled epsilon-greedy least-squares learning converges almost surely to the complete-information feedback Nash equilibrium in infinite-horizon nonzero-sum linear-quadratic stochastic games, at a rate gove...

  2. Bridging Finite and Infinite-Horizon Nash Equilibria in Linear Quadratic Games

    cs.MA 2025-08 conditional novelty 6.0 of 10

    The finite-horizon Riccati recursion's fixed points equal infinite-horizon Nash equilibria, and its cycles, if any, are periodic Nash equilibria.

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