Associate Professor, Department of Engineering Science, University of Oxford
Tutorial Fellow, St. Anne's College
email: reaching jakob at gmail dot com [no generic ("I'd like to...") emails, please!]
Note to potential applicants:
If you are interested in pursuing a PhD ("DPhil") at my lab, please apply to both the Engineering Department (deadline is early December!) and the AIMS CDT (deadline is mid January). Make sure to list me as a supervisor for the direct application.
If you are wondering whether my lab is the right place for you, please take a look at my publications on Google Scholar and watch some of my talks on the internet and only email me if there are specific follow-up questions. As a scientist, I do like to hear about non-obvious insights and interesting follow-up suggestions to previous work.
For any emails please put the code "d48b8eb9a99bc6" into the subject line to confirm that you have read these instructions.
Thanks a lot!
Jakob
Research Interests
(Deep) (Multi-Agent) (Reinforcement) Learning, Human-AI Coordination , Emergent Communication, Search, Planning, Game Theory
News!
I started as an Associate Professor at the Engineering Science Department at the University of Oxford and St. Anne's College.
Publications, Preprints and links to code etc:
[NOTE: This is gets updated sporadically and hence is stale (by design). Please check Google Scholar for recent papers / publications]
2022
Tons of new papers here: https://foersterlab.com/research/
"Centralized Model and Exploration Policy for Multi-Agent RL" [paper]
Q Zhang, C Lu, A Garg, JN Foerster
International Conference on Autonomous Agents and Multiagent Systems, 2022
"Lyapunov Exponents for Diversity in Differentiable Games" [paper]
J Lorraine, P Vicol, J Parker-Holder, T Kachman, L Metz, JN Foerster
International Conference on Autonomous Agents and Multiagent Systems, 2022
2021
"K-level Reasoning for Zero-Shot Coordination in Hanabi" [paper]
B Cui, H Hu, L Pineda, JN Foerster
Neural Information Processing Systems, 2021
"Replay-Guided Adversarial Environment Design" [paper, Tweet Explainer]
M Jiang, M Dennis, J Parker-Holder, J Foerster, E Grefenstette, T Rocktäschel
Neural Information Processing Systems, 2021
"Neural Pseudo-Label Optimism for the Bank Loan Problem" [paper, code, Tweet Explainer]
A Pacchiano, S Singh, E Chou, A Berg, JN Foerster
Neural Information Processing Systems, 2021
"Off-Belief Learning" [paper, code]
H Hu, A Lerer, B Cui, L Pineda, D Wu, N Brown, JN Foerster
International Conference on Machine Learning, 2021
"Trajectory diversity for zero-shot coordination" [paper, code]
A Lupu, B Cui, H Hu, JN Foerster
International Conference on Machine Learning, 2021
"A New Formalism, Method and Open Issues for Zero-Shot Coordination" [paper, code]
J Treutlein, M Dennis, C Oesterheld, JN Foerster
International Conference on Machine Learning, 2021
2020
"Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian" [paper, code 1, code 2, code 3]
J Parker-Holder*, L Metz, C Resnick, H Hu, A Lerer, A Letcher, A Peysakhovich, A Pacchiano, JN Foerster*
Neural Information Processing Systems, 2020
"“Other-Play” for Zero-Shot Coordination" [paper, code]
H Hu*, A Lerer, A Peysakhovich, JN Foerster*
International Conference on Machine Learning, 2020
2019
"On the interaction between supervision and self-play in emergent communication " [paper]
R Lowe*, A Gupta*, JN Foerster, D Kiela, J Pineau
International Conference on Learning Representations, 2020
"Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning " [paper, code]
H Hu, JN Foerster
International Conference on Learning Representations, 2020
"Improving Policies via Search in Cooperative Partially Observable Games " [paper, code, blog post]
A Lerer, H Hu, JN Foerster, N Brown
AAAI Conference on Artificial Intelligence, 2020
"Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods" [paper]
OM Camburu*, E Giunchiglia*, JN Foerster, T Lukasiewicz, P Blunsom
preprint
"Capacity, Bandwidth, and Compositionality in Emergent Language Learning" [paper]
C Resnick*, A Gupta*, JN Foerster, AM Dai, K Cho
International Conference on Autonomous Agents and Multiagent Systems, 2020
"Differentiable Game Mechanics" [paper]
A Letcher, D Balduzzi, S Racaniere, J Martens, JN Foerster, K Tuyls, T Graepel
Journal of Machine Learning Research
"Robust Domain Randomization for Reinforcement Learning" [paper, code]
RB Slaoui, WR Clements, JN Foerster, S Toth
preprint
"Exploratory Combinatorial Optimization with Reinforcement Learning" [paper, code ]
TD Barrett, WR Clements, JN Foerster, AI Lvovsky
AAAI Conference on Artificial Intelligence, 2020
"Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning" [paper, code]
G Farquhar, S Whiteson, JN Foerster
Advances in Neural Information Processing Systems, 2019
"A Survey of Reinforcement Learning Informed by Natural Language" [paper]
J Luketina, N Nardelli, G Farquhar, JN Foerster, J Andreas, E Grefenstette, S Whiteson, T Rocktäschel
IJCAI Survey Track, 2019
"The StarCraft Multi-Agent Challenge" [paper, code, blog]
M Samvelyan*, T Rashid*, C Schroeder de Witt, G Farquhar, N Nardelli, T. Rudner, C Hung, P Torr, JN Foerster, S Whiteson
International Conference on Autonomous Agents and Multiagent Systems, 2019
"The Hanabi Challenge: A New Frontier for AI Research" [paper, code, blog]
N Bard*, JN Foerster*, S Chandar, N Burch, M Lanctot, HF Song, E Parisotto, V Dumoulin, S Moitra, E Hughes, I Dunning, S Mourad, H Larochelle, MG Bellemare, M Bowling
Artificial Intelligence (AIJ)
"Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning" [paper, matrix game code ]
JN Foerster*, FH Song*, E Hughes, N Burch, I Dunning, S Whiteson, M Botvinick, M Bowling
International Conference on Machine Learning, 2019
"A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs" [paper]
J Mao*, JN Foerster*, T Rocktäschel, G Farquhar, M Al-Shedivat, S Whiteson
International Conference on Machine Learning, 2019
"On the Pitfalls of Measuring Emergent Communication" [paper]
R Lowe, JN Foerster , YL Boureau, J Pineau, Y Dauphin
International Conference on Autonomous Agents and Multiagent Systems, 2019
2018
"Multi-Agent Common Knowledge Reinforcement Learning" [paper]
CAS de Witt*, JN Foerster* , G Farquhar, PHS Torr, W Boehmer, S Whiteson
Advances in Neural Information Processing Systems, 2019
"Pommerman: A multi-agent playground" [paper]
C Resnick, W Eldridge, D Ha, D Britz, JN Foerster, J Togelius, K Cho, J Bruna
NeurIPS 2018 Competition track
"Stable Opponent Shaping in Differentiable Games" [paper]
A Letcher, JN Foerster, D Balduzzi, T Rocktäschel, S Whiteson
International Conference on Learning Representations, 2019
"DiCE: The Infinitely Differentiable Monte-Carlo Estimator" [paper, code, pyro support]
JN Foerster, G Farquhar*, M Al-Shedivat*, T Rocktäschel, EP Xing, S Whiteson
International Conference on Machine Learning, 2018
"QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning" [link]
T Rashid*, M Samvelyan*, CS de Witt, G Farquhar, JN Foerster, S Whiteson
International Conference on Machine Learning, 2018
"The Mechanics of n-Player Differentiable Games" [link, code ]
D Balduzzi, S Racaniere, J Martens, JN Foerster, K Tuyls, T Graepel
International Conference on Machine Learning, 2018, Best Paper Runner-Up Award
"Learning with Opponent-Learning Awareness" [paper, video, slides, blog post, code, pytorch implementation]
JN Foerster*, RY Chen*, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch
International Conference on Autonomous Agents and Multiagent Systems, 2018
"Counterfactual Multi-Agent Policy Gradients" [link]
JN Foerster*, G Farquhar*, T Afouras, N Nardelli, S Whiteson
AAAI Conference on Artificial Intelligence 2018, Outstanding Student Paper Award
2017
"Stabilising experience replay for deep multi-agent reinforcement learning" [paper, video, media coverage]
JN Foerster*, N Nardelli*, G Farquhar, P Torr, P Kohli, S Whiteson
International Conference on Machine Learning, 2017
"Input switched affine networks: An RNN architecture designed for interpretability" [paper, video, code]
JN Foerster*, J Gilmer*, J Sohl-Dickstein, J Chorowski, D Sussillo
International Conference on Machine Learning, 2017
"Nonlinear Computation in Deep Linear Networks" [link]
JN Foerster
OpenAI Blog
"Fake News in Social Networks" [link, news coverage, code]
C Aymanns, JN Foerster, CP Georg
arXiv preprint arXiv:1708.06233
2016
"Learning to communicate with deep multi-agent reinforcement learning" [paper, video, slides, code, pytorch implementation, pytorch implementation in Colab- LTC in your browser! ]
JN Foerster*, IA Assael*, N de Freitas, S Whiteson
Advances in Neural Information Processing Systems, 2016, 2137-2145
"Learning to communicate to solve riddles with deep distributed recurrent q-networks" [link, news coverage, podcast]
JN Foerster*, YM Assael*, N de Freitas, S Whiteson
IJCAI 2016 Deep Learning Workshop
2015
"Three-dimensional head-direction coding in the bat brain" [link]
A Finkelstein, D Derdikman, A Rubin, JN Foerster, L Las, N Ulanovsky
Nature 517 (7533), 159
2011
"Control of vocal and respiratory patterns in birdsong: dissection of forebrain and brainstem mechanisms using temperature" [link]
AS Andalman*, JN Foerster*, MS Fee
PLoS One 6 (9), e25461