Dynamic signaling games with quadratic criteria under Nash and Stackelberg equilibria

Creative Commons License

Saritas S., Yuksel S., Gezici S.

AUTOMATICA, vol.115, 2020 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 115
  • Publication Date: 2020
  • Doi Number: 10.1016/j.automatica.2020.108883
  • Journal Name: AUTOMATICA
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Aqualine, Communication Abstracts, Compendex, Computer & Applied Sciences, Information Science and Technology Abstracts, INSPEC, MathSciNet, zbMATH, DIALNET, Library, Information Science & Technology Abstracts (LISTA)
  • Keywords: Signaling games, Stochastic networked control, Game theory, Information theory, INFORMATION, COMMUNICATION, DESIGN
  • Middle East Technical University Affiliated: No


This paper considers dynamic (multi-stage) signaling games involving an encoder and a decoder who have subjective models on the cost functions. We consider both Nash (simultaneous-move) and Stackelberg (leader-follower) equilibria of dynamic signaling games under quadratic criteria. For the multi-stage scalar cheap talk, we show that the final stage equilibrium is always quantized and under further conditions the equilibria for all time stages must be quantized. In contrast, the Stackelberg equilibria are always fully revealing. In the multi-stage signaling game where the transmission of a Gauss-Markov source over a memoryless Gaussian channel is considered, affine policies constitute an invariant subspace under best response maps for Nash equilibria; whereas the Stackelberg equilibria always admit linear policies for scalar sources but such policies may be nonlinear for multi-dimensional sources. We obtain an explicit recursion for optimal linear encoding policies for multi-dimensional sources, and derive conditions under which Stackelberg equilibria are informative. (C) 2020 Elsevier Ltd. All rights reserved.