Foerster, Jakob

48 publications

NeurIPS 2024 Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning Jonathan Cook, Chris Lu, Edward Hughes, Joel Z. Leibo, Jakob Foerster

NeurIPS 2024 BAM! Just like That: Simple and Efficient Parameter Upcycling for Mixture of Experts Qizhen Zhang, Nikolas Gritsch, Dwaraknath Gnaneshwar, Simon Guo, David Cairuz, Bharat Venkitesh, Jakob Foerster, Phil Blunsom, Sebastian Ruder, Ahmet Üstün, Acyr Locatelli

UAI 2024 Computing Low-Entropy Couplings for Large-Support Distributions Samuel Sokota, Dylan Sam, Christian Witt, Spencer Compton, Jakob Foerster, J. Zico Kolter

NeurIPS 2024 Discovering Preference Optimization Algorithms with and for Large Language Models Chris Lu, Samuel Holt, Claudio Fanconi, Alex J. Chan, Jakob Foerster, Mihaela van der Schaar, Robert Tjarko Lange

NeurIPS 2024 JaxMARL: Multi-Agent RL Environments and Algorithms in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Ravi Hammond, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Foerster

NeurIPS 2024 No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery Alex Rutherford, Michael Beukman, Timon Willi, Bruno Lacerda, Nick Hawes, Jakob Foerster

NeurIPS 2024 Rainbow 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 Foerster, Tim Rocktäschel, Roberta Raileanu

NeurIPS 2024 Recurrent Reinforcement Learning with Memoroids Steven Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob Foerster, Amanda Prorok

NeurIPS 2023 Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design Matthew T Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Greg Farquhar, Shimon Whiteson, Jakob Foerster

NeurIPS 2023 SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob Foerster, Shimon Whiteson

NeurIPS 2023 Similarity-Based Cooperative Equilibrium Caspar Oesterheld, Johannes Treutlein, Roger B Grosse, Vincent Conitzer, Jakob Foerster

NeurIPS 2023 Structured State Space Models for In-Context Reinforcement Learning Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Foerster, Satinder P. Singh, Feryal Behbahani

ICML 2022 COLA: Consistent Learning with Opponent-Learning Awareness Timon Willi, Alistair Hp Letcher, Johannes Treutlein, Jakob Foerster

ICML 2022 Communicating via Markov Decision Processes Samuel Sokota, Christian A Schroeder De Witt, Maximilian Igl, Luisa M Zintgraf, Philip Torr, Martin Strohmeier, Zico Kolter, Shimon Whiteson, Jakob Foerster

NeurIPS 2022 Discovered Policy Optimisation Chris Lu, Jakub Kuba, Alistair Letcher, Luke Metz, Christian Schroeder de Witt, Jakob Foerster

NeurIPS 2022 Equivariant Networks for Zero-Shot Coordination Darius Muglich, Christian Schroeder de Witt, Elise van der Pol, Shimon Whiteson, Jakob Foerster

ICML 2022 Evolving Curricula with Regret-Based Environment Design Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel

ICML 2022 Generalized Beliefs for Cooperative AI Darius Muglich, Luisa M Zintgraf, Christian A Schroeder De Witt, Shimon Whiteson, Jakob Foerster

NeurIPS 2022 Grounding Aleatoric Uncertainty for Unsupervised Environment Design Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob Foerster

NeurIPS 2022 Influencing Long-Term Behavior in Multiagent Reinforcement Learning Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P How

ICML 2022 Mirror Learning: A Unifying Framework of Policy Optimisation Jakub Grudzien, Christian A Schroeder De Witt, Jakob Foerster

ICML 2022 Model-Free Opponent Shaping Christopher Lu, Timon Willi, Christian A Schroeder De Witt, Jakob Foerster

NeurIPS 2022 Nocturne: A Scalable Driving Benchmark for Bringing Multi-Agent Learning One Step Closer to the Real World Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob Foerster

NeurIPS 2022 Off-Team Learning Brandon Cui, Hengyuan Hu, Andrei Lupu, Samuel Sokota, Jakob Foerster

NeurIPS 2022 Proximal Learning with Opponent-Learning Awareness Stephen Zhao, Chris Lu, Roger B Grosse, Jakob Foerster

NeurIPS 2022 Self-Explaining Deviations for Coordination Hengyuan Hu, Samuel Sokota, David Wu, Anton Bakhtin, Andrei Lupu, Brandon Cui, Jakob Foerster

ICML 2021 A New Formalism, Method and Open Issues for Zero-Shot Coordination Johannes Treutlein, Michael Dennis, Caspar Oesterheld, Jakob Foerster

NeurIPS 2021 K-Level Reasoning for Zero-Shot Coordination in Hanabi Brandon Cui, Hengyuan Hu, Luis Pineda, Jakob Foerster

NeurIPS 2021 Neural Pseudo-Label Optimism for the Bank Loan Problem Aldo Pacchiano, Shaun Singh, Edward Chou, Alex Berg, Jakob Foerster

ICML 2021 Off-Belief Learning Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, Jakob Foerster

NeurIPS 2021 Replay-Guided Adversarial Environment Design Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel

ICML 2021 Trajectory Diversity for Zero-Shot Coordination Andrei Lupu, Brandon Cui, Hengyuan Hu, Jakob Foerster

JMLR 2020 Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid, Mikayel Samvelyan, Christian Schroeder de Witt, Gregory Farquhar, Jakob Foerster, Shimon Whiteson

ICLR 2020 On the Interaction Between Supervision and Self-Play in Emergent Communication Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau

NeurIPS 2020 Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alexander Peysakhovich, Aldo Pacchiano, Jakob Foerster

ICML 2020 “Other-Play” for Zero-Shot Coordination Hengyuan Hu, Adam Lerer, Alex Peysakhovich, Jakob Foerster

ICML 2019 A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs Jingkai Mao, Jakob Foerster, Tim Rocktäschel, Maruan Al-Shedivat, Gregory Farquhar, Shimon Whiteson

ICML 2019 Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning Jakob Foerster, Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew Botvinick, Michael Bowling

JMLR 2019 Differentiable Game Mechanics Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel

ICMLW 2019 Learning to Learn to Communicate Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau

NeurIPS 2019 Loaded DiCE: Trading Off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning Gregory Farquhar, Shimon Whiteson, Jakob Foerster

NeurIPS 2019 Multi-Agent Common Knowledge Reinforcement Learning Christian Schroeder de Witt, Jakob Foerster, Gregory Farquhar, Philip Torr, Wendelin Boehmer, Shimon Whiteson

ICLR 2019 Stable Opponent Shaping in Differentiable Games Alistair Letcher, Jakob Foerster, David Balduzzi, Tim Rocktäschel, Shimon Whiteson

ICML 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric Xing, Shimon Whiteson

ICML 2018 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, Shimon Whiteson

ICML 2018 The Mechanics of N-Player Differentiable Games David Balduzzi, Sebastien Racaniere, James Martens, Jakob Foerster, Karl Tuyls, Thore Graepel

ICML 2017 Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson

NeurIPS 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning Jakob Foerster, Ioannis Alexandros Assael, Nando de Freitas, Shimon Whiteson