Selected Papers
• "A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement
Learning"[arxiv]
Zun Li, Michael P.
Wellman In Proceedings of Thirty-Third International Joint Conference on Artificial
Intelligence (IJCAI),
2024.
Best Paper Award of Adaptive and Learning Agents (ALA) Workshop at
AAMAS,
2024.
Keywords: Meta-Strategies / Meta-Game Analysis, Evaluation, Bootstrapping
Statistics, Empirical Game-Theoretic Analysis, Search
• "Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and
Negotiation Games (Extended Abstract)"[arXiv]
Zun Li, Marc Lanctot, Kevin McKee, Luke
Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P.
Wellman
In Proceedings of Twenty-Second International Conference on Autonomous Agents and Multiagent
Systems
(AAMAS), 2023.
Keywords: Extensive-Form Games, Nash Bargaining Solutions, Game-Tree Search,
Population-Based Reinforcement Learning, Negotiation
• "Evolution Strategies for Approximate Solution of Bayesian Games"[PDF][TALK][SLIDES][POSTER]
Zun Li, Michael P.
Wellman In Proceedings of Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI),
2021.
Keywords: Bayesian Games, Equilibrium Computation, Deep Learning, Evolutionary
Computation, Auctions
• "Structure Learning for Approximate Solution of Many-Player Games" [PDF][SLIDES][POSTER]
Zun Li, Michael P.
Wellman
In Proceedings of Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
Keywords: Normal-Form Games, Equilibrium Computation, Machine Learning, Graphical
Models
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