Jakob Nicolaus Foerster

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 22

Top Topics

Temporal Difference

Eligibility Traces

Reinforcement Learning

Partially Observable Domains

Top Venues

Trans. Mach. Learn. Res.

Publications

Yat Long Lo, Biswa Sengupta, Jakob Nicolaus Foerster, Michael Noukhovitch
Learning Multi-Agent Communication with Contrastive Learning. ICLR (2024)
Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster
Can Learned Optimization Make Reinforcement Learning Less Difficult? CoRR (2024)
Matteo Gallici, Mattie Fellows, Benjamin Ellis, Bartomeu Pou, Ivan Masmitja, Jakob Nicolaus Foerster, Mario Martin
Simplifying Deep Temporal Difference Learning. CoRR (2024)
Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster
Discovering Temporally-Aware Reinforcement Learning Algorithms. ICLR (2024)
Silvia Sapora, Gokul Swamy, Chris Lu, Yee Whye Teh, Jakob Nicolaus Foerster
EvIL: Evolution Strategies for Generalisable Imitation Learning. CoRR (2024)
Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster
Discovering Temporally-Aware Reinforcement Learning Algorithms. CoRR (2024)
Andrei Lupu, Chris Lu, Jarek Liesen, Robert Tjarko Lange, Jakob Nicolaus Foerster
Behaviour Distillation. ICLR (2024)
Tim Franzmeyer, Stephen Marcus McAleer, João F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schröder de Witt
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks. ICLR (2024)
Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Nicolaus Foerster, João F. Henriques
Select to Perfect: Imitating desired behavior from large multi-agent data. ICLR (2024)
Brandon Cui, Andrei Lupu, Samuel Sokota, Hengyuan Hu, David J. Wu, Jakob Nicolaus Foerster
Adversarial Diversity in Hanabi. ICLR (2023)
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 (2023)
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 Adversarial Environment Design. CoRR (2023)
Isaac Liao, Rumen Dangovski, Jakob Nicolaus Foerster, Marin Soljacic
Learning to Optimize Quasi-Newton Methods. Trans. Mach. Learn. Res. 2023 (2023)
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 Reinforcement Learning. ICLR (2023)
Christian Schröder de Witt, Samuel Sokota, J. Zico Kolter, Jakob Nicolaus Foerster, Martin Strohmeier
Perfectly Secure Steganography Using Minimum Entropy Coupling. ICLR (2023)
Mingwei Ma, Jizhou Liu, Samuel Sokota, Max Kleiman-Weiner, Jakob Nicolaus Foerster
Learning Intuitive Policies Using Action Features. ICML (2023)
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)
Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster
Adversarial Cheap Talk. ICML (2023)
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
JaxMARL: Multi-Agent RL Environments in JAX. CoRR (2023)
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 (2023)
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)
Stephen Zhao, Chris Lu, Roger Baker Grosse, Jakob Nicolaus Foerster
Proximal Learning With Opponent-Learning Awareness. CoRR (2022)