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Publication search results
found 202 matches
- 2024
- Panagiotis Tsiotras, Matthew C. Gombolay, Jakob Foerster:
Editorial: Decision-making and planning for multi-agent systems. Frontiers Robotics AI 11 (2024) - Tim Franzmeyer, Aleksandar Shtedritski, Samuel Albanie, Philip Torr, João F. Henriques, Jakob N. Foerster:
HelloFresh: LLM Evalutions on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits. ACL (Findings) 2024: 12702-12716 - Paul Barde, Jakob Foerster, Derek Nowrouzezahrai, Amy Zhang:
A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem. AAMAS 2024: 141-150 - Kitty Fung, Qizhen Zhang, Chris Lu, Jia Wan, Timon Willi, Jakob N. Foerster:
Analysing the Sample Complexity of Opponent Shaping. AAMAS 2024: 623-631 - Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti, Chris Lu, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster:
Scaling Opponent Shaping to High Dimensional Games. AAMAS 2024: 1001-1010 - Linas Nasvytis, Kai Sandbrink, Jakob N. Foerster, Tim Franzmeyer, Christian Schröder de Witt:
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection. AAMAS 2024: 1445-1453 - 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 T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster:
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. AAMAS 2024: 2444-2446 - 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 - 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 - Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster:
Discovering Temporally-Aware Reinforcement Learning Algorithms. ICLR 2024 - Yat Long Lo, Biswa Sengupta, Jakob Nicolaus Foerster, Michael Noukhovitch:
Learning Multi-Agent Communication with Contrastive Learning. ICLR 2024 - Andrei Lupu, Chris Lu, Jarek Liesen, Robert Tjarko Lange, Jakob Nicolaus Foerster:
Behaviour Distillation. ICLR 2024 - Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows, Minqi Jiang, Michael D. Dennis, Jakob Nicolaus Foerster:
Refining Minimax Regret for Unsupervised Environment Design. ICML 2024 - Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster:
Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. ICML 2024 - Andrew Jesson, Chris Lu, Gunshi Gupta, Nicolas Beltran-Velez, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal:
ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages. ICML 2024 - Michael T. Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob Nicolaus Foerster:
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning. ICML 2024 - Johan Samir Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro:
Mixtures of Experts Unlock Parameter Scaling for Deep RL. ICML 2024 - Silvia Sapora, Gokul Swamy, Chris Lu, Yee Whye Teh, Jakob Nicolaus Foerster:
EvIL: Evolution Strategies for Generalisable Imitation Learning. ICML 2024 - Ziyang Zhang, Qizhen Zhang, Jakob Nicolaus Foerster:
PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition. ICML 2024 - Uljad Berdica, Matthew Thomas Jackson, Niccolò Enrico Veronese, Jakob N. Foerster, Perla Maiolino:
Reinforcement Learning Controllers for Soft Robots Using Learned Environments. RoboSoft 2024: 933-939 - 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 abs/2402.01088 (2024) - 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) - Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert T. Lange, Shimon Whiteson, Jakob Nicolaus Foerster:
Discovering Temporally-Aware Reinforcement Learning Algorithms. CoRR abs/2402.05828 (2024) - 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 Scaling for Deep RL. CoRR abs/2402.08609 (2024) - 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) - Ravi Hammond, Dustin Craggs, Mingyu Guo, Jakob Foerster, Ian D. Reid:
Symmetry-Breaking Augmentations for Ad Hoc Teamwork. CoRR abs/2402.09984 (2024) - Michael Beukman, Samuel Coward, Michael T. Matthews, Mattie Fellows, Minqi Jiang, Michael Dennis, Jakob N. Foerster:
Refining Minimax Regret for Unsupervised Environment Design. CoRR abs/2402.12284 (2024) - Michael T. Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob N. Foerster:
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning. CoRR abs/2402.16801 (2024) - 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 Raileanu:
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. CoRR abs/2402.16822 (2024) - 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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