Gregory Farquhar

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 39

Top Topics

Temporal Difference

Gradient Estimators

Reinforcement Learning

Top Venues

Publications

Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. NeurIPS (2023)
Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. CoRR (2023)
Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal Behbahani, Tom Schaul, André Barreto, Simon Osindero
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. ICML (2022)
Risto Vuorio, Jacob Beck, Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar
An Investigation of the Bias-Variance Tradeoff in Meta-Gradients. CoRR (2022)
Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
Transient Non-stationarity and Generalisation in Deep Reinforcement Learning. ICLR (2021)
Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
Proper Value Equivalence. NeurIPS (2021)
Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado van Hasselt, David Silver
Self-Consistent Models and Values. CoRR (2021)
Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. ICML (2021)
Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal Behbahani, Tom Schaul, André Barreto, Simon Osindero
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. CoRR (2021)
Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. CoRR (2021)
Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
Proper Value Equivalence. CoRR (2021)
Gregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado Philip van Hasselt, David Silver
Self-Consistent Models and Values. NeurIPS (2021)
Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. NeurIPS (2020)
Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve
Growing Action Spaces. ICML (2020)
Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
The Impact of Non-stationarity on Generalisation in Deep Reinforcement Learning. CoRR (2020)
Tabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson
Weighted QMIX: Expanding Monotonic Value Function Factorisation. CoRR (2020)
Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. CoRR (2020)
Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. J. Mach. Learn. Res. 21 (2020)
Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve
Growing Action Spaces. CoRR (2019)
Jingkai Mao, Jakob N. Foerster, Tim Rocktäschel, Maruan Al-Shedivat, Gregory Farquhar, Shimon Whiteson
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs. ICML (2019)
Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning. NeurIPS (2019)
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
The StarCraft Multi-Agent Challenge. AAMAS (2019)
Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning. CoRR (2019)
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
The StarCraft Multi-Agent Challenge. CoRR (2019)
Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel
A Survey of Reinforcement Learning Informed by Natural Language. CoRR (2019)
Christian Schröder de Witt, Jakob N. Foerster, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson
Multi-Agent Common Knowledge Reinforcement Learning. NeurIPS (2019)
Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel
A Survey of Reinforcement Learning Informed by Natural Language. IJCAI (2019)
Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson
DiCE: The Infinitely Differentiable Monte-Carlo Estimator. ICLR (Workshop) (2018)
Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. CoRR (2018)
Jakob N. Foerster, Christian A. Schröder de Witt, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson
Multi-Agent Common Knowledge Reinforcement Learning. CoRR (2018)
Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson
DiCE: The Infinitely Differentiable Monte-Carlo Estimator. CoRR (2018)
Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. ICML (2018)
Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson
DiCE: The Infinitely Differentiable Monte Carlo Estimator. ICML (2018)
Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson
Counterfactual Multi-Agent Policy Gradients. AAAI (2018)
Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson
TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning. ICLR (Poster) (2018)
Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson
TreeQN and ATreeC: Differentiable Tree Planning for Deep Reinforcement Learning. CoRR (2017)
Jakob N. Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning. ICML (2017)
Jakob N. Foerster, Nantas Nardelli, Gregory Farquhar, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning. CoRR (2017)
Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, Shimon Whiteson
Counterfactual Multi-Agent Policy Gradients. CoRR (2017)