most citedRandomise Alone, Reach as a Team

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cs.GT2026

Algorithms for Equilibria in Concurrent Stopping Games

Léonard Brice, Thomas A. Henzinger, K. S. Thejaswini

Concurrent games are a standard model for multi-agent systems, with Nash equilibrium as their central solution concept. The associated \emph{constrained existence problem}---does a…

cs.GT2026

Equilibria in Multiplayer Graph Games: An Algorithmic Study

Léonard Brice

To verify the robustness of a program or protocol, it is common in the computer science community to rely on the theoretical framework of game theory. In particular, if one seeks t…

cs.GT2026★ 1 cited

Randomise Alone, Reach as a Team

Léonard Brice, Thomas A. Henzinger, Alipasha Montaseri +2

We study concurrent graph games where n players cooperate against an opponent to reach a set of target states. Unlike traditional settings, we study distributed randomisation: team…

cs.GT2026★ 1 cited

Dicey Games: Shared Sources of Randomness in Distributed Systems

Léonard Brice, Thomas A. Henzinger, K. S. Thejaswini

Consider a 4-player version of Matching Pennies where a team of three players competes against the Devil. Each player simultaneously says "Heads" or "Tails". The team wins if all f…

cs.GT2025

ε-Stationary Nash Equilibria in Multi-player Stochastic Graph Games

Ali Asadi, Léonard Brice, Krishnendu Chatterjee +1

A strategy profile in a multi-player game is a Nash equilibrium if no player can unilaterally deviate to achieve a strictly better payoff. A profile is an -Nash equilibrium if n…

cs.GT2025

Finding equilibria: simpler for pessimists, simplest for optimists

Léonard Brice, Thomas Henzinger, K. S. Thejaswini

We consider simple stochastic games with terminal-node rewards and multiple players, who have differing perceptions of risk. Specifically, we study risk-sensitive equilibria (RSEs)…