VISER: A Tractable Solution Concept for Games with Information Asymmetry

TL;DR

VISER is a new solution concept for games with information asymmetry, enabling prediction and strategic defense in security and multi-agent scenarios, computable efficiently via linear programming.

Contribution

The paper introduces VISER, a novel tractable solution concept for asymmetric information games, extending it to Markov games and providing polynomial-time computation methods.

Findings

VISER strategies can be computed independently in polynomial time.

VISER effectively predicts game outcomes under information asymmetry.

Extension to Markov games maintains computational efficiency.

Abstract

Many real-world games suffer from information asymmetry: one player is only aware of their own payoffs while the other player has the full game information. Examples include the critical domain of security games and adversarial multi-agent reinforcement learning. Information asymmetry renders traditional solution concepts such as Strong Stackelberg Equilibrium (SSE) and Robust-Optimization Equilibrium (ROE) inoperative. We propose a novel solution concept called VISER (Victim Is Secure, Exploiter best-Responds). VISER enables an external observer to predict the outcome of such games. In particular, for security applications, VISER allows the victim to better defend itself while characterizing the most damaging attacks available to the attacker. We show that each player's VISER strategy can be computed independently in polynomial time using linear programming (LP). We also extend VISER to its Markov-perfect counterpart for Markov games, which can be solved efficiently using a series of LPs.