Gregory Farquhar

According to our database, Gregory Farquhar authored at least 25 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design.

Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

An Investigation of the Bias-Variance Tradeoff in Meta-Gradients.

Risto Vuorio, Jacob Beck, Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar

CoRR, 2022

Model-Value Inconsistency as a Signal for Epistemic Uncertainty.

Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero

Proceedings of the International Conference on Machine Learning, 2022

2021

Proper Value Equivalence.

Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self-Consistent Models and Values.

Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado Philip van Hasselt, David Silver

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning.

Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar

Proceedings of the 38th International Conference on Machine Learning, 2021

Transient Non-stationarity and Generalisation in Deep Reinforcement Learning.

Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.

Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson

J. Mach. Learn. Res., 2020

Weighted QMIX: Expanding Monotonic Value Function Factorisation.

Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson

CoRR, 2020

The Impact of Non-stationarity on Generalisation in Deep Reinforcement Learning.

Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson

CoRR, 2020

Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.

Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Growing Action Spaces.

Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning.

Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster

CoRR, 2019

Multi-Agent Common Knowledge Reinforcement Learning.

Christian Schröder de Witt, Jakob N. Foerster, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning.

Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 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

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs.

Jingkai Mao, Jakob N. Foerster, Tim Rocktäschel, Maruan Al-Shedivat, Gregory Farquhar, Shimon Whiteson

Proceedings of the 36th International Conference on Machine Learning, 2019

The StarCraft Multi-Agent Challenge.

Mikayel Samvelyan, Tabish Rashid, Christian Schröder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob N. Foerster, Shimon Whiteson

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.

Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson

Proceedings of the 35th International Conference on Machine Learning, 2018

DiCE: The Infinitely Differentiable Monte-Carlo Estimator.

Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson

Proceedings of the 6th International Conference on Learning Representations, 2018

TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning.

Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson

Proceedings of the 6th International Conference on Learning Representations, 2018

Counterfactual Multi-Agent Policy Gradients.

Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

TreeQN and ATreeC: Differentiable Tree Planning for Deep Reinforcement Learning.

Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson

CoRR, 2017

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning.

Jakob N. Foerster, Nantas Nardelli, Gregory Farquhar, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson

CoRR, 2017

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning.

Jakob N. Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson

Proceedings of the 34th International Conference on Machine Learning, 2017