Chris Lu

According to our database, Chris Lu authored at least 22 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Revisiting Recurrent Reinforcement Learning with Memory Monoids.

Steven D. Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob N. Foerster, Amanda Prorok

CoRR, 2024

Discovering Temporally-Aware Reinforcement Learning Algorithms.

Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

CoRR, 2024

Meta-learning the mirror map in policy mirror descent.

Carlo Alfano, Sebastian Towers, Silvia Sapora, Chris Lu, Patrick Rebeschini

CoRR, 2024

The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games.

Jake Levi, Chris Lu, Timon Willi, Christian Schröder de Witt, Jakob N. Foerster

CoRR, 2024

JaxMARL: Multi-Agent RL Environments and Algorithms 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, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Scaling Opponent Shaping to High Dimensional Games.

Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti, Chris Lu, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Analysing the Sample Complexity of Opponent Shaping.

Kitty Fung, Qizhen Zhang, Chris Lu, Jia Wan, Timon Willi, Jakob N. Foerster

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Leading the Pack: N-player Opponent Shaping.

Alexandra Souly, Timon Willi, Akbir Khan, Robert Kirk, Chris Lu, Edward Grefenstette, Tim Rocktäschel

CoRR, 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 Schröder 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

CoRR, 2023

ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages.

Andrew Jesson, Chris Lu, Gunshi Gupta, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal

CoRR, 2023

Arbitrary Order Meta-Learning with Simple Population-Based Evolution.

Chris Lu, Sebastian Towers, Jakob N. Foerster

CoRR, 2023

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design.

Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adversarial Cheap Talk.

Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

Proceedings of the International Conference on Machine Learning, 2023

JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading.

Sascha Yves Frey, Kang Li, Peer Nagy, Silvia Sapora, Christopher Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu

Proceedings of the 4th ACM International Conference on AI in Finance, 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

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.

Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Proximal Learning With Opponent-Learning Awareness.

Stephen Zhao, Chris Lu, Roger B. Grosse, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Discovered Policy Optimisation.

Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Model-Free Opponent Shaping.

Christopher Lu, Timon Willi, Christian A. Schröder de Witt, Jakob N. Foerster

Proceedings of the International Conference on Machine Learning, 2022

Centralized Model and Exploration Policy for Multi-Agent RL.

Qizhen Zhang, Christopher Lu, Animesh Garg, Jakob N. Foerster

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2019

Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity.

Deepak Pathak, Christopher Lu, Trevor Darrell, Phillip Isola, Alexei A. Efros

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019