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Mirror Learning: A Unifying Framework of Policy Optimisation.
Jakub Grudzien Kuba, Christian Schröder de Witt, Jakob N. Foerster: Mirror Learning: A Unifying Framework of Policy Optimisation. CoRR abs/2201.02373 (2022)
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Proximal Learning With Opponent-Learning Awareness.
Stephen Zhao, Chris Lu, Roger B. Grosse, Jakob N. Foerster: Proximal Learning With Opponent-Learning Awareness. NeurIPS 2022
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Equivariant Networks for Zero-Shot Coordination.
Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster: Equivariant Networks for Zero-Shot Coordination. NeurIPS 2022
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Influencing Long-Term Behavior in Multiagent Reinforcement Learning.
Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How: Influencing Long-Term Behavior in Multiagent Reinforcement Learning....
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Grounding Aleatoric Uncertainty for Unsupervised Environment Design.
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster: Grounding Aleatoric Uncertainty for Unsupervised Environment...
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Self-Explaining Deviations for Coordination.
Hengyuan Hu, Samuel Sokota, David J. Wu, Anton Bakhtin, Andrei Lupu, Brandon Cui, Jakob N. Foerster: Self-Explaining Deviations for Coordination. NeurIPS 2022
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Off-Team Learning.
Brandon Cui, Hengyuan Hu, Andrei Lupu, Samuel Sokota, Jakob N. Foerster: Off-Team Learning. NeurIPS 2022
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Discovered Policy Optimisation.
Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster: Discovered Policy Optimisation. NeurIPS 2022
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COLA: Consistent Learning with Opponent-Learning Awareness.
Timon Willi, Alistair Letcher, Johannes Treutlein, Jakob N. Foerster: COLA: Consistent Learning with Opponent-Learning Awareness. ICML 2022: 23804-23831
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Communicating via Markov Decision Processes.
Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster: Communicating via Markov...
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Evolving Curricula with Regret-Based Environment Design.
Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel: Evolving Curricula with Regret-Based Environment Design. ICML 2022: 17473-17498
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Generalized Beliefs for Cooperative AI.
Darius Muglich, Luisa M. Zintgraf, Christian A. Schröder de Witt, Shimon Whiteson, Jakob N. Foerster: Generalized Beliefs for Cooperative AI. ICML 2022: 16062-16082
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Model-Free Opponent Shaping.
Christopher Lu, Timon Willi, Christian A. Schröder de Witt, Jakob N. Foerster: Model-Free Opponent Shaping. ICML 2022: 14398-14411
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Mirror Learning: A Unifying Framework of Policy Optimisation.
Jakub Grudzien Kuba, Christian A. Schröder de Witt, Jakob N. Foerster: Mirror Learning: A Unifying Framework of Policy Optimisation. ICML 2022: 7825-7844
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A Fine-Tuning Approach to Belief State Modeling.
Samuel Sokota, Hengyuan Hu, David J. Wu, J. Zico Kolter, Jakob Nicolaus Foerster, Noam Brown: A Fine-Tuning Approach to Belief State Modeling. ICLR 2022
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Centralized Model and Exploration Policy for Multi-Agent RL.
Qizhen Zhang, Christopher Lu, Animesh Garg, Jakob N. Foerster: Centralized Model and Exploration Policy for Multi-Agent RL. AAMAS 2022: 1500-1508
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Lyapunov Exponents for Diversity in Differentiable Games.
Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster: Lyapunov Exponents for Diversity in Differentiable Games. AAMAS 2022: 842-852
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Scaling Opponent Shaping to High Dimensional Games.
Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti, Chris Lu, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster: Scaling Opponent Shaping to High Dimensional Games. CoRR abs/2312.12568 (2023)
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JaxMARL: Multi-Agent RL Environments in JAX.
Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay,...
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Discovering General Reinforcement Learning Algorithms with Adversarial...
Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster: Discovering General Reinforcement Learning Algorithms with...
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Generative AI for End-to-End Limit Order Book Modelling: A Token-Level...
Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster: Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative...
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JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale...
Sascha Frey, Kang Li, Peer Nagy, Silvia Sapora, Chris Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu: JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement...
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Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank...
Elena Gal, Shaun Singh, Aldo Pacchiano, Ben Walker, Terry Lyons, Jakob N. Foerster: Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank Loan Problem. CoRR abs/2308.08051 (2023)
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Learning to Communicate using Contrastive Learning.
Yat Long Lo, Biswa Sengupta, Jakob N. Foerster, Michael Noukhovitch: Learning to Communicate using Contrastive Learning. CoRR abs/2307.01403 (2023)
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ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive...
Andrew Jesson, Chris Lu, Gunshi Gupta, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal: ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages. CoRR abs/2306.01460 (2023)
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Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning.
Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson: Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. CoRR abs/2303.10733 (2023)
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Arbitrary Order Meta-Learning with Simple Population-Based Evolution.
Chris Lu, Sebastian Towers, Jakob N. Foerster: Arbitrary Order Meta-Learning with Simple Population-Based Evolution. CoRR abs/2303.09478 (2023)
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Structured State Space Models for In-Context Reinforcement Learning.
Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani: Structured State Space Models for In-Context Reinforcement Learning. CoRR...
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MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning.
Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Roberta Raileanu, Tim Rocktäschel: MAESTRO: Open-Ended Environment Design for Multi-Agent...
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Learning Intuitive Policies Using Action Features.
Mingwei Ma, Jizhou Liu, Samuel Sokota, Max Kleiman-Weiner, Jakob Nicolaus Foerster: Learning Intuitive Policies Using Action Features. ICML 2023: 23358-23372
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Adversarial Cheap Talk.
Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster: Adversarial Cheap Talk. ICML 2023: 22917-22941
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Perfectly Secure Steganography Using Minimum Entropy Coupling.
Christian Schröder de Witt, Samuel Sokota, J. Zico Kolter, Jakob Nicolaus Foerster, Martin Strohmeier: Perfectly Secure Steganography Using Minimum Entropy Coupling. ICLR 2023
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MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning.
Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Roberta Raileanu, Tim Rocktäschel: MAESTRO: Open-Ended Environment Design for Multi-Agent...
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Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning.
Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson: Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. ICLR 2023
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Adversarial Diversity in Hanabi.
Brandon Cui, Andrei Lupu, Samuel Sokota, Hengyuan Hu, David J. Wu, Jakob Nicolaus Foerster: Adversarial Diversity in Hanabi. ICLR 2023
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JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale...
Sascha Yves Frey, Kang Li, Peer Nagy, Silvia Sapora, Christopher Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu: JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale...
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Generative AI for End-to-End Limit Order Book Modelling: A Token-Level...
Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster: Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative...
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Discovering Temporally-Aware Reinforcement Learning Algorithms.
Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster: Discovering Temporally-Aware Reinforcement Learning Algorithms. CoRR abs/2402.05828 (2024)
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Analysing the Sample Complexity of Opponent Shaping.
Kitty Fung, Qizhen Zhang, Chris Lu, Jia Wan, Timon Willi, Jakob N. Foerster: Analysing the Sample Complexity of Opponent Shaping. CoRR abs/2402.05782 (2024)
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The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg...
Jake Levi, Chris Lu, Timon Willi, Christian Schröder de Witt, Jakob N. Foerster: The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games. CoRR...
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Revisiting Recurrent Reinforcement Learning with Memory Monoids.
Steven D. Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob N. Foerster, Amanda Prorok: Revisiting Recurrent Reinforcement Learning with Memory Monoids. CoRR abs/2402.09900 (2024)
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Mixtures of Experts Unlock Parameter Scaling for Deep RL.
Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro: Mixtures of Experts Unlock Parameter...
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Similarity-based cooperative equilibrium.
Caspar Oesterheld, Johannes Treutlein, Roger B. Grosse, Vincent Conitzer, Jakob N. Foerster: Similarity-based cooperative equilibrium. NeurIPS 2023
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SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement...
Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob N. Foerster, Shimon Whiteson: SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement...
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Structured State Space Models for In-Context Reinforcement Learning.
Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani: Structured State Space Models for In-Context Reinforcement Learning. NeurIPS 2023
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Discovering General Reinforcement Learning Algorithms with Adversarial...
Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster: Discovering General Reinforcement Learning Algorithms with...
View ArticleRainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts.
Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Tim Rocktäschel, Roberta...
View ArticleCraftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning.
Michael Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew T. Jackson, Samuel Coward, Jakob N. Foerster: Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning....
View ArticleRefining Minimax Regret for Unsupervised Environment Design.
Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows, Minqi Jiang, Michael Dennis, Jakob N. Foerster: Refining Minimax Regret for Unsupervised Environment Design. CoRR abs/2402.12284 (2024)
View ArticleJaxUED: A simple and useable UED library in Jax.
Samuel Coward, Michael Beukman, Jakob N. Foerster: JaxUED: A simple and useable UED library in Jax. CoRR abs/2403.13091 (2024)
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