MASAGE: Model-Agnostic Sequential and Adaptive Game Estimation

Yunian Pan, Guanze Peng, Juntao Chen, Quanyan Zhu

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

Abstract

Zero-sum games have been used to model cybersecurity scenarios between an attacker and a defender. However, unknown and uncertain environments have made it difficult to rely on a prescribed zero-sum game to capture the interactions between the players. In this work, we aim to estimate and recover an unknown matrix game that encodes the uncertainties of nature and opponent based on the knowledge of historical games and the current observations of game outcomes. The proposed approach effectively transfers the past experiences that are encoded as expert games to estimate and inform future game plays. We formulate the game knowledge transfer and estimation problem as a sequential least-square problem. We characterize the structural properties of the problem and show that the non-convex problem has well-behaved gradient and Hessian under mild assumptions. We propose gradient-based methods to enable dynamic and adaptive estimation of the unknown game. A case study is used to corroborate the results and illustrate the behavior of the proposed algorithm.

Original languageEnglish (US)
Title of host publicationDecision and Game Theory for Security - 11th International Conference, GameSec 2020, Proceedings
EditorsQuanyan Zhu, John S. Baras, Radha Poovendran, Juntao Chen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages365-384
Number of pages20
ISBN (Print)9783030647926
DOIs
StatePublished - 2020
Event11th Conference on Decision and Game Theory for Security, GameSec 2020 - College Park, United States
Duration: Oct 28 2020Oct 30 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12513 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Conference on Decision and Game Theory for Security, GameSec 2020
CountryUnited States
CityCollege Park
Period10/28/2010/30/20

Keywords

  • Gradient-based methods
  • Least-square estimation
  • Neural networks
  • Security games
  • Sensitivity analysis
  • Zero-sum games

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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