Inertial game dynamics and applications to constrained optimization
Rida Laraki, Panayotis Mertikopoulos

TL;DR
This paper introduces a second-order inertial game dynamics based on Riemannian geometry, demonstrating its stability properties and applications to constrained optimization and equilibrium attraction.
Contribution
It develops a new inertial replicator dynamics framework using Hessian-Riemannian metrics, ensuring well-posedness and stability in game-theoretic and optimization contexts.
Findings
Inertial dynamics are not well-posed under Shahshahani metric.
Alternative Hessian-Riemannian metrics can ensure well-posedness.
Strict equilibria attract solutions in multi- and single-population games.
Abstract
Aiming to provide a new class of game dynamics with good long-term rationality properties, we derive a second-order inertial system that builds on the widely studied "heavy ball with friction" optimization method. By exploiting a well-known link between the replicator dynamics and the Shahshahani geometry on the space of mixed strategies, the dynamics are stated in a Riemannian geometric framework where trajectories are accelerated by the players' unilateral payoff gradients and they slow down near Nash equilibria. Surprisingly (and in stark contrast to another second-order variant of the replicator dynamics), the inertial replicator dynamics are not well-posed; on the other hand, it is possible to obtain a well-posed system by endowing the mixed strategy space with a different Hessian-Riemannian (HR) metric structure, and we characterize those HR geometries that do so. In the…
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