Foerster, Jakob N

10 publications

IJCAI 2025 Combining Code Generating Large Language Models and Self-Play to Iteratively Refine Strategies in Games Yoram Bachrach, Edan Toledo, Karen Hambardzumyan, Despoina Magka, Martin Josifoski, Minqi Jiang, Jakob N. Foerster, Roberta Raileanu, Tatiana Shavrina, Nicola Cancedda, Avraham Ruderman, Katie Millican, Andrei Lupu, Rishi Hazra

NeurIPS 2024 Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps Benjamin Ellis, Matthew T. Jackson, Andrei Lupu, Alexander D. Goldie, Mattie Fellows, Shimon Whiteson, Jakob N. Foerster

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

NeurIPS 2024 The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning Anya Sims, Cong Lu, Jakob N. Foerster, Yee Whye Teh

AAAI 2020 Exploratory Combinatorial Optimization with Reinforcement Learning Thomas D. Barrett, William R. Clements, Jakob N. Foerster, A. I. Lvovsky

AAAI 2020 Improving Policies via Search in Cooperative Partially Observable Games Adam Lerer, Hengyuan Hu, Jakob N. Foerster, Noam Brown

ICLR 2020 Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning Hengyuan Hu, Jakob N Foerster

IJCAI 2019 A Survey of Reinforcement Learning Informed by Natural Language Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel

AAAI 2018 Counterfactual Multi-Agent Policy Gradients Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson

ICML 2017 Input Switched Affine Networks: An RNN Architecture Designed for Interpretability Jakob N. Foerster, Justin Gilmer, Jascha Sohl-Dickstein, Jan Chorowski, David Sussillo