Version 1
: Received: 12 November 2019 / Approved: 13 November 2019 / Online: 13 November 2019 (11:47:14 CET)
Version 2
: Received: 14 November 2019 / Approved: 18 November 2019 / Online: 18 November 2019 (07:34:00 CET)
e Oliveira Jr., H. A. Designing Strategic Games with Preestablished Nash Equilibrium through Artificial Inference and Global Learning. Jahrbücher für Nationalökonomie und Statistik, 2021, 241, 463–476. https://doi.org/10.1515/jbnst-2020-0040.
e Oliveira Jr., H. A. Designing Strategic Games with Preestablished Nash Equilibrium through Artificial Inference and Global Learning. Jahrbücher für Nationalökonomie und Statistik, 2021, 241, 463–476. https://doi.org/10.1515/jbnst-2020-0040.
e Oliveira Jr., H. A. Designing Strategic Games with Preestablished Nash Equilibrium through Artificial Inference and Global Learning. Jahrbücher für Nationalökonomie und Statistik, 2021, 241, 463–476. https://doi.org/10.1515/jbnst-2020-0040.
e Oliveira Jr., H. A. Designing Strategic Games with Preestablished Nash Equilibrium through Artificial Inference and Global Learning. Jahrbücher für Nationalökonomie und Statistik, 2021, 241, 463–476. https://doi.org/10.1515/jbnst-2020-0040.
Abstract
This work presents significant results obtained by the application of global optimization techniques to the design of finite, normal form games with mixed strategies. To that end, the Fuzzy ASA global optimization method is applied to several design examples of strategic games, demonstrating its effectiveness in obtaining payoff functions whose corresponding games present a previously established Nash equilibrium. In other words, the game designer becomes able to choose a convenient Nash equilibrium for a generic finite state strategic game and the proposed method computes payoff functions that will realize the desired equilibrium, making it possible for the players to reach the favorable conditions represented by the chosen equilibrium. Considering that game theory is a very significant approach for modeling interactions between competing agents, and Nash equilibrium represents a powerful solution concept, portraying situations in which joint strategies are optimal in the sense that players cannot benefit from individually modifying their current strategies provided that other players do not change their strategies as well, it is natural to infer that the proposed method may be very useful for strategists in general. In summary, it is a genuine instance of artificial inference of payoff functions after a process of global machine learning, applied to their numerical components.
Keywords
Nash equilibria; game and mechanism design; simulated annealing; fuzzy ASA; artificial inference; global machine learning
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
