Research Interests

(Deep) (Multi-Agent) (Reinforcement) Learning, Human-AI Coordination , Emergent Communication, Search, Planning, Game Theory


News!

I am extremely grateful to have been awarded a CIFAR AI Chair! Link

Old News

I am joining the CS department at the University of Toronto (Scarborough Campus) and the Vector Institute in the academic year of 20/21. I am looking for exceptional PhD / Master students and postdocs. Please apply via U of T. Note, while my undergraduate teaching will take place at Scarborough, all research will take place at the downtown campus and Vector institute, where PhD - / Master students / postdocs will be located. Until my move to Toronto I will keep working at Facebook AI Research in Menlo Park.


Publications, Preprints and links to code etc:

2020

"“Other-Play” for Zero-Shot Coordination" [paper]

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