“Human-AI Coordination via Human-Regularized Search and Learning”, Hu Et Al 2022

“Human-AI Coordination via Human-Regularized Search and Learning”⁠, Hengyuan Hu, David J. Wu, Adam Lerer, Jakob Foerster, Noam Brown2022-10-11 (MARL; similar)

“Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabi”, Grooten Et Al 2022

“Is Vanilla Policy Gradient Overlooked? Analyzing Deep Reinforcement Learning for Hanabi”⁠, Bram Grooten, Jelle Wemmenhove, Maurice Poot, Jim Portegies2022-03-22 (model-free RL; similar)

“On-the-fly Strategy Adaptation for Ad-hoc Agent Coordination”, Zand Et Al 2022

“On-the-fly Strategy Adaptation for ad-hoc Agent Coordination”⁠, Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts2022-03-08 (model-based RL⁠, Bayes; similar)

“Any-Play: An Intrinsic Augmentation for Zero-Shot Coordination”, Lucas & Allen2022

“Any-Play: An Intrinsic Augmentation for Zero-Shot Coordination”⁠, Keane Lucas, Ross E. Allen2022-01-28 (RL exploration; similar)

“Conditional Imitation Learning for Multi-Agent Games”, Shih Et Al 2022

“Conditional Imitation Learning for Multi-Agent Games”⁠, Andy Shih, Stefano Ermon, Dorsa Sadigh2022-01-05 (similar)

“Reinforcement Learning on Human Decision Models for Uniquely Collaborative AI Teammates”, Kantack2021

“Reinforcement Learning on Human Decision Models for Uniquely Collaborative AI Teammates”⁠, Nicholas Kantack2021-11-18 (model-based RL; similar)

“Scalable Online Planning via Reinforcement Learning Fine-Tuning”, Fickinger Et Al 2021

“Scalable Online Planning via Reinforcement Learning Fine-Tuning”⁠, Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart Russell, Noam Brown2021-09-30 (meta-learning⁠, AlphaGo; similar)

“Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi”, Siu Et Al 2021

“Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi”⁠, Ho Chit Siu, Jaime D. Pena, Edenna Chen, Yutai Zhou, Victor J. Lopez, Kyle Palko, Kimberlee C. Chang2021-07-15 (similar)

“Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings”, Hu Et Al 2021

“Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings”⁠, Hengyuan Hu, Adam Lerer, Noam Brown, Jakob Foerster2021-06-16 (similar)

“On the Critical Role of Conventions in Adaptive Human-AI Collaboration”, Shih Et Al 2021

“On the Critical Role of Conventions in Adaptive Human-AI Collaboration”⁠, Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh2021-04-07 (similar)

“Off-Belief Learning”, Hu Et Al 2021

“Off-Belief Learning”⁠, Hengyuan Hu, Adam Lerer, Brandon Cui, David Wu, Luis Pineda, Noam Brown, Jakob Foerster2021-03-06 (similar)

“Continuous Coordination As a Realistic Scenario for Lifelong Learning”, Nekoei Et Al 2021

“Continuous Coordination As a Realistic Scenario for Lifelong Learning”⁠, Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar2021-03-04 (similar)

“The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games”, Yu Et Al 2021

“The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games”⁠, Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre Bayen, Yi Wu2021-03-02 (backlinks; similar)

“Theory of Mind for Deep Reinforcement Learning in Hanabi”, Fuchs Et Al 2021

“Theory of Mind for Deep Reinforcement Learning in Hanabi”⁠, Andrew Fuchs, Michael Walton, Theresa Chadwick, Doug Lange2021-01-22 (similar)

“Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi”, Canaan Et Al 2020

“Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi”⁠, Rodrigo Canaan, Xianbo Gao, Julian Togelius, Andy Nealen, Stefan Menzel2020-04-28 (similar)

“Evaluating the Rainbow DQN Agent in Hanabi With Unseen Partners”, Canaan Et Al 2020

“Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners”⁠, Rodrigo Canaan, Xianbo Gao, Youjin Chung, Julian Togelius, Andy Nealen, Stefan Menzel2020-04-28 (model-free RL; similar)

“ “Other-Play” For Zero-Shot Coordination”, Hu Et Al 2020

“"Other-Play" for Zero-Shot Coordination”⁠, Hengyuan Hu, Adam Lerer, Alex Peysakhovich, Jakob Foerster2020-03-06 (similar)

“Improving Policies via Search in Cooperative Partially Observable Games”, Lerer Et Al 2019

“Improving Policies via Search in Cooperative Partially Observable Games”⁠, Adam Lerer, Hengyuan Hu, Jakob Foerster, Noam Brown2019-12-05 (similar)

“Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning”, Hu & Foerster2019

“Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning”⁠, Hengyuan Hu, Jakob N. Foerster2019-12-04 (similar)

“The Hanabi Challenge: A New Frontier for AI Research”, Bard Et Al 2019

“The Hanabi Challenge: A New Frontier for AI Research”⁠, Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto2019-02-01 (similar)

“Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning”, Foerster Et Al 2018

“Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning”⁠, Jakob N. Foerster, Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew Botvinick2018-11-04 (model-based RL⁠, Bayes; similar)

Wikipedia

1. Hanabi (card game)