Lu, Chris

32 publications

ICLR 2025 Kinetix: Investigating the Training of General Agents Through Open-Ended Physics-Based Control Tasks Michael Matthews, Michael Beukman, Chris Lu, Jakob Nicolaus Foerster

ICLR 2025 Learning Mirror Maps in Policy Mirror Descent Carlo Alfano, Sebastian Rene Towers, Silvia Sapora, Chris Lu, Patrick Rebeschini

NeurIPS 2025 NAVIX: Scaling MiniGrid Environments with JAX Eduardo Pignatelli, Jarek Luca Liesen, Robert Tjarko Lange, Chris Lu, Pablo Samuel Castro, Laura Toni

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

ICLR 2024 Behaviour Distillation Andrei Lupu, Chris Lu, Jarek Luca Liesen, Robert Tjarko Lange, Jakob Nicolaus Foerster

NeurIPS 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander D. Goldie, Chris Lu, Matthew T. Jackson, Shimon Whiteson, Jakob N. Foerster

ICMLW 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander D. Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster

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

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

ICLR 2024 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

ICML 2024 EvIL: Evolution Strategies for Generalisable Imitation Learning Silvia Sapora, Gokul Swamy, Chris Lu, Yee Whye Teh, Jakob Nicolaus Foerster

ICMLW 2024 Higher Order and Self-Referential Evolution for Population-Based Methods Samuel Coward, Chris Lu, Alistair Letcher, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster

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

ICMLW 2024 Learning In-Context Decision Making with Synthetic MDPs Akarsh Kumar, Chris Lu, Louis Kirsch, Phillip Isola

ICML 2024 ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages Andrew Jesson, Chris Lu, Gunshi Gupta, Nicolas Beltran-Velez, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal

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

ICML 2023 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

ICMLW 2023 Analyzing the Sample Complexity of Model-Free Opponent Shaping Kitty Fung, Qizhen Zhang, Chris Lu, Timon Willi, Jakob Nicolaus Foerster

ICLR 2023 Discovering Evolution Strategies via Meta-Black-Box Optimization Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag

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

NeurIPSW 2023 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

NeurIPSW 2023 JaxMARL: Multi-Agent RL Environments in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster

NeurIPSW 2023 Leading the Pack: N-Player Opponent Shaping Alexandra Souly, Timon Willi, Akbir Khan, Robert Kirk, Chris Lu, Edward Grefenstette, Tim Rocktäschel

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

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

ICMLW 2022 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

NeurIPSW 2022 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

NeurIPSW 2022 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

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

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

ICLRW 2022 Model-Free Opponent Shaping Chris Lu, Timon Willi, Christian Schroeder de Witt, Jakob Nicolaus Foerster

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