Game Theory

Is Nash Equilibrium Approximator Learnable?
In this paper, we investigate the learnability of the function approximator that approximates Nash equilibrium (NE) for games generated …
PDF Cite
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems
In order for agents in multi-agent systems (MAS) to be safe, they need to take into account the risks posed by the actions of other …
PDF Cite
Regret-Minimizing Double Oracle for Extensive-Form Games
By incorporating regret minimization, double oracle methods have demonstrated rapid convergence to Nash Equilibrium (NE) in normal-form …
PDF Cite
Learning to Shape Rewards using a Game of Two Partners
Reward shaping (RS) is a powerful method in reinforcement learning (RL) for overcoming the problem of sparse or uninformative rewards. …
PDF Cite
Online Double Oracle
Solving strategic games with huge action space is a critical yet under-explored topic in economics, operations research and artificial …
PDF Cite
On the Convergence of Fictitious Play: A Decomposition Approach
Fictitious play (FP) is one of the most fundamental game-theoretical learning frameworks for computing Nash equilibrium in n-player …
PDF Cite
Measuring the Non-Transitivity in Chess
In this paper, we quantify the non-transitivity in chess using human game data. Specifically, we perform non-transitivity …
PDF Cite