4.7 Article

Distributed Population Dynamics for Searching Generalized Nash Equilibria of Population Games With Graphical Strategy Interactions

Journal

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 52, Issue 5, Pages 3263-3272

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2021.3062827

Keywords

Statistics; Sociology; Games; Nash equilibrium; Dynamic scheduling; Communication networks; Heuristic algorithms; Dynamical communication networks; Nash equilibrium seeking; population dynamics; potential game

Funding

  1. National Natural Science Foundation of China [61873088, 61503130]

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This article explores the modeling of population games and dynamics with static and dynamic graphical communication structures. It introduces the concept of generalized Nash equilibria for population games with graphical strategy interactions and establishes the equivalence between the set of generalized Nash equilibria and the set of rest points of its distributed population dynamics. The study also analyzes the conditions for convergence to generalized Nash equilibrium and Nash equilibrium for distributed population dynamics with both static and dynamical graphical structures.
Evolutionary games and population dynamics are finding increasing applications in design learning and control protocols for a variety of resource allocation problems. The implicit requirement for full communication has been the main limitation of the evolutionary game dynamic approach in engineering tasks with various information constraints. This article intends to build population games and dynamics with both static and dynamical graphical communication structures. To this end, we formulate a population game model with graphical strategy interactions and derive its corresponding population dynamics. In particular, we first introduce the concept of generalized Nash equilibria for population games with graphical strategy interactions, and establish the equivalence between the set of generalized Nash equilibria and the set of rest points of its distributed population dynamics. Furthermore, the conditions for convergence to generalized Nash equilibrium and particularly to Nash equilibrium are obtained for the distributed population dynamics with both static and dynamical graphical structures. These results provide a new approach to design distributed Nash equilibrium seeking algorithms for population games with both static and dynamical communication networks, and hence, expand the applicability of the population game dynamics in the design of learning and control protocols under distributed circumstances.

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