Visible to the public Sequential decomposition of Stochastic Stackelberg games

TitleSequential decomposition of Stochastic Stackelberg games
Publication TypeConference Paper
Year of Publication2022
AuthorsVasal, Deepanshu
Conference Name2022 American Control Conference (ACC)
Date Publishedjun
Keywordsdynamic games of asymmetric information, Games, Heuristic algorithms, Markov processes, pubcrawl, Resiliency, Scalability, security, Stochastic Computing Security, Stochastic Stackelberg games
AbstractIn this paper, we consider a discrete-time stochastic Stackelberg game where there is a defender (also called leader) who has to defend a target and an attacker (also called follower). The attacker has a private type that evolves as a controlled Markov process. The objective is to compute the stochastic Stackelberg equilibrium of the game where defender commits to a strategy. The attacker's strategy is the best response to the defender strategy and defender's strategy is optimum given the attacker plays the best response. In general, computing such equilibrium involves solving a fixed-point equation for the whole game. In this paper, we present an algorithm that computes such strategies by solving lower dimensional fixed-point equations for each time t. Based on this algorithm, we compute the Stackelberg equilibrium of a security example.
Citation Keyvasal_sequential_2022