On Adaptive-Gain Control of Replicator Dynamics in Population Games

Fuente: arXiv
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Main Authors: Zino, Lorenzo, Ye, Mengbin, Rizzo, Alessandro, Calafiore, Giuseppe Carlo
Format: Preprint
Published: 2023
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_version_ 1866917809261379584
author Zino, Lorenzo
Ye, Mengbin
Rizzo, Alessandro
Calafiore, Giuseppe Carlo
author_facet Zino, Lorenzo
Ye, Mengbin
Rizzo, Alessandro
Calafiore, Giuseppe Carlo
contents Controlling evolutionary game-theoretic dynamics is a problem of paramount importance for the systems and control community, with several applications spanning from social science to engineering. Here, we study a population of individuals who play a generic 2-action matrix game, and whose actions evolve according to a replicator equation -- a nonlinear ordinary differential equation that captures salient features of the collective behavior of the population. Our objective is to steer such a population to a specified equilibrium that represents a desired collective behavior -- e.g., to promote cooperation in the prisoner's dilemma. To this aim, we devise an adaptive-gain controller, which regulates the system dynamics by adaptively changing the entries of the payoff matrix of the game. The adaptive-gain controller is tailored according to distinctive features of the game, and conditions to guarantee global convergence to the desired equilibrium are established.
format Preprint
id arxiv_https___arxiv_org_abs_2306_14469
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle On Adaptive-Gain Control of Replicator Dynamics in Population Games
Zino, Lorenzo
Ye, Mengbin
Rizzo, Alessandro
Calafiore, Giuseppe Carlo
Systems and Control
Dynamical Systems
Optimization and Control
Controlling evolutionary game-theoretic dynamics is a problem of paramount importance for the systems and control community, with several applications spanning from social science to engineering. Here, we study a population of individuals who play a generic 2-action matrix game, and whose actions evolve according to a replicator equation -- a nonlinear ordinary differential equation that captures salient features of the collective behavior of the population. Our objective is to steer such a population to a specified equilibrium that represents a desired collective behavior -- e.g., to promote cooperation in the prisoner's dilemma. To this aim, we devise an adaptive-gain controller, which regulates the system dynamics by adaptively changing the entries of the payoff matrix of the game. The adaptive-gain controller is tailored according to distinctive features of the game, and conditions to guarantee global convergence to the desired equilibrium are established.
title On Adaptive-Gain Control of Replicator Dynamics in Population Games
topic Systems and Control
Dynamical Systems
Optimization and Control
url https://arxiv.org/abs/2306.14469