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Autor(es):
Bueno, L. F. ; Haeser, G. ; Kolossoski, O.
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: SIAM JOURNAL ON OPTIMIZATION; v. 35, n. 3, p. 31-pg., 2025-01-01.
Resumo

A common strategy for solving an unconstrained two-player Nash equilibrium problem with continuous variables is applying Newton's method to the system obtained by the corresponding first-order necessary optimality conditions. However, when taking into account the game dynamics, it is not clear what is the goal of each player when considering they are taking their current decision following Newton's iterates. In this paper we provide an interpretation for Newton's iterate as follows: instead of minimizing the quadratic approximation of the objective functions parameterized by the other player current decision (the Jacobi-type strategy), we show that the Newton iterate follows this approach but with the objective function parameterized by a prediction of the other player action. This interpretation allows us to present a new Newtonian algorithm where a backtracking procedure is introduced in order to guarantee that the computed Newtonian directions, for each player, are descent directions for the corresponding parameterized functions. Thus, besides favoring global convergence, our algorithm also favors true minimizers instead of maximizers or saddle points, unlike the standard Newton method, which does not consider the minimization structure of the problem in the nonconvex case. Thus, our method is more robust compared to other Jacobi-type strategies or the pure Newtonian approach, which is corroborated by our numerical experiments. We also present a proof of the well-definiteness of the algorithm under some standard assumptions, together with a preliminary analysis of its convergence properties taking into account the game dynamics. (AU)

Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
Beneficiário:Francisco Louzada Neto
Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
Processo FAPESP: 22/05803-3 - Problemas de corte, empacotamento, dimensionamento de lotes, programação da produção, roteamento e localização e suas integrações em contextos industriais e logísticos
Beneficiário:Reinaldo Morabito Neto
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 23/08706-1 - Métodos computacionais de otimização
Beneficiário:Ernesto Julián Goldberg Birgin
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 15/02528-8 - Métodos do tipo Newton para otimização linear e não linear
Beneficiário:Luis Felipe Cesar da Rocha Bueno
Modalidade de apoio: Auxílio à Pesquisa - Regular
Processo FAPESP: 21/05007-0 - Métodos numéricos para equilíbrio de Nash com critério de descenso
Beneficiário:Oliver Kolossoski
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado