Research Interests

(Deep) (Multi-Agent) (Reinforcement) Learning, 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 fall of 2020. I am looking for exceptional PhD / Master students and postdocs. Please apply via U of T and only email me in exceptional cases! 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