Learning Equilibrium with Estimated Payoffs in Population Games

التفاصيل البيبلوغرافية
العنوان: Learning Equilibrium with Estimated Payoffs in Population Games
المؤلفون: Park, Shinkyu
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Systems and Control
الوصف: We study a multi-agent decision problem in population games, where agents select from multiple available strategies and continually revise their selections based on the payoffs associated with these strategies. Unlike conventional population game formulations, we consider a scenario where agents must estimate the payoffs through local measurements and communication with their neighbors. By employing task allocation games -- dynamic extensions of conventional population games -- we examine how errors in payoff estimation by individual agents affect the convergence of the strategy revision process. Our main contribution is an analysis of how estimation errors impact the convergence of the agents' strategy profile to equilibrium. Based on the analytical results, we propose a design for a time-varying strategy revision rate to guarantee convergence. Simulation studies illustrate how the proposed method for updating the revision rate facilitates convergence to equilibrium.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2407.06328
رقم الأكسشن: edsarx.2407.06328
قاعدة البيانات: arXiv