Hierarchical multistage Gaussian signaling games in noncooperative communication and control systems

Muhammed O. Sayin, Emrah Akyol, Tamer Başar

Research output: Contribution to journalArticle

Abstract

We analyze in this paper finite horizon hierarchical signaling games between (information provider) senders and (decision maker) receivers in a dynamic environment. The underlying information evolves in time while sender and receiver interact repeatedly. Different from the classical communication (control) models, however, the sender (sensor) and the receiver (controller) have different objectives and there is a hierarchy between the players such that the sender leads the game by announcing his policies beforehand. He needs to anticipate the reaction of the receiver and the impact of the actions on the horizon while controlling the transparency of the disclosed information at each interaction. With quadratic cost functions and multivariate Gaussian processes, evolving according to first order auto-regressive models, we show that memoryless “linear” sender signaling rules are optimal (in the sense of game-theoretic hierarchical equilibrium) within the general class of measurable policies in the noncooperative communication context. In the noncooperative control context, we also analyze the hierarchical equilibrium for linear signaling rules and provide an algorithm to compute the optimal linear signaling rules numerically with global optimality guarantees.

Original languageEnglish (US)
Pages (from-to)9-20
Number of pages12
JournalAutomatica
Volume107
DOIs
StatePublished - Sep 2019

Keywords

  • Communications
  • Dynamic games
  • Hierarchical decision making
  • Information theory
  • Kalman filters
  • LQG control
  • Signaling games
  • Stackelberg games

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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