Control of parametric games

Carmel Fiscko, Brian Swenson, Soummya Kar, Bruno Sinopoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


This work studies a class of multi-player games in which the players' decisions can be influenced by a superplayer. We define a game with n players and parameterized utilities u (., a) where the superplayer controls the value of a. The regular players follow Markovian repeated play dynamics that encompass a wide class of learning dynamics including strict best response. The objective of the superplayer is to control a dynamically to achieve a desired outcome in the game-play, which in this work we define as the realization of target joint strategies. We introduce the class of parametric games and reformulate the superplayer control problem as a Markov decision process (MDP). Reachability criteria are developed, allowing the superplayer to determine which game-play may occur with positive probability. With a reachable goal joint strategy, a cost-optimal policy can be computed using standard tools in dynamic programming. A sample MDP reward function is presented such that a reachable target joint strategy is guaranteed to be played almost surely. Finally, an application in a cyber-security context is provided to illustrate the use of the proposed methodology and its effectiveness.

Original languageEnglish (US)
Title of host publication2019 18th European Control Conference, ECC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9783907144008
StatePublished - Jun 2019
Event18th European Control Conference, ECC 2019 - Naples, Italy
Duration: Jun 25 2019Jun 28 2019

Publication series

Name2019 18th European Control Conference, ECC 2019


Conference18th European Control Conference, ECC 2019

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Control and Optimization


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