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Jun Wang

Is Nash Equilibrium Approximator Learnable?
Large Sequence Models for Sequential Decision-Making: A Survey
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning
MANSA: Learning Fast and Slow in Multi-Agent Systems
Learning to Shape Rewards using a Game of Two Partners
On the complexity of computing Markov perfect equilibrium in general-sum stochastic games
A game-theoretic approach to multi-agent trust region optimization
Contextual Transformer for Offline Meta Reinforcement Learning
Scalable Model-based Policy Optimization for Decentralized Networked Systems
Online Double Oracle
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning
Offline Pre-trained Multi-agent Decision Transformer
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem
On the Convergence of Fictitious Play: A Decomposition Approach
Measuring the Non-Transitivity in Chess
Neural Auto-Curricula in Two-Player Zero-Sum Games
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning
Online Markov Decision Processes with Non-oblivious Strategic Adversary
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning
Settling the Variance of Multi-Agent Policy Gradients

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