Timon Willi
Timon Willi
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Cited by
Cited by
Model-Free Opponent Shaping
C Lu, T Willi, CAS De Witt, J Foerster
International Conference on Machine Learning, 2022
Consistent Learning with Opponent-Learning Awareness
T Willi*, AH Letcher*, J Treutlein*, J Foerster
International Conference on Machine Learning, 2022
Recurrent Neural Processes
T Willi, J Masci, J Schmidhuber, C Osendorfer
arXiv preprint arXiv:1906.05915, 2019
Adversarial Cheap Talk
C Lu, T Willi, A Letcher, JN Foerster
Decision Awareness in Reinforcement Learning Workshop at ICML 2022, 2022
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
A Rutherford*, B Ellis*, M Gallici*, J Cook*, A Lupu*, G Ingvarsson*, ...
Proceedings of the 23rd International Conference on Autonomous Agents and …, 2024
Mixtures of Experts Unlock Parameter Scaling for Deep RL
JSO Ceron*, G Sokar*, T Willi*, C Lyle, J Farebrother, JN Foerster, ...
Forty-first International Conference on Machine Learning (spotlight, 3.5%), 2024
Scaling Opponent Shaping to High Dimensional Games
A Khan*, T Willi*, N Kwan*, A Tacchetti, C Lu, E Grefenstette, ...
arXiv preprint arXiv:2312.12568, 2023
Analysing the Sample Complexity of Opponent Shaping
K Fung, Q Zhang, C Lu, J Wan, T Willi, J Foerster
arXiv preprint arXiv:2402.05782, 2024
Pax: Scalable Opponent Shaping in Jax
T Willi, A Khan, N Kwan, M Samvelyan, C Lu, J Foerster
Leading the Pack: N-player Opponent Shaping
A Souly, T Willi, A Khan, R Kirk, C Lu, E Grefenstette, T Rocktäschel
arXiv preprint arXiv:2312.12564, 2023
Mixture of Experts in a Mixture of RL settings
T Willi, J Obando-Ceron, J Foerster, K Dziugaite, PS Castro
arXiv preprint arXiv:2406.18420, 2024
The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games
J Levi, C Lu, T Willi, CS de Witt, J Foerster
arXiv preprint arXiv:2402.01088, 2024
Evaluation of Word Embeddings for Stance Detection in Tweets
T Willi
Bachelor's Thesis, University of Zurich, 2017
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