Distributed Population Dynamics: Optimization and Control Applications

Julian Barreiro-Gomez, Germán Obando, Nicanor Quijano

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Population dynamics have been widely used in the design of learning and control systems for networked engineering applications, where the information dependency among elements of the network has become a relevant issue. Classic population dynamics (e.g., replicator, logit choice, Smith, and projection) require full information to evolve to the solution (Nash equilibrium). The main reason is that classic population dynamics are deduced by assuming well-mixed populations, which limits the applications where this theory can be implemented. In this paper, we extend the concept of population dynamics for nonwell-mixed populations in order to deal with distributed information structures that are characterized by noncomplete graphs. Although the distributed population dynamics proposed in this paper use partial information, they preserve similar characteristics and properties of their classic counterpart. Specifically, we prove mass conservation and convergence to Nash equilibrium. To illustrate the performance of the proposed dynamics, we show some applications in the solution of optimization problems, classic games, and the design of distributed controllers.

Original languageEnglish (US)
Article number7419636
Pages (from-to)304-314
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume47
Issue number2
DOIs
StatePublished - Feb 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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