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Jakob Foerster — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Jakob Foerster
43
papers ·
2021
citations ·
30
h-index
University of Oxford · Science Oxford
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Counterfactual Multi-Agent Policy Gradients
2017 · 478 citations
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
2018 · 475 citations
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
2020 · 429 citations
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
2017 · 335 citations
"Other-Play" for Zero-Shot Coordination
2020 · 33 citations
Fake News in Social Networks
2017 · 20 citations
Discovered Policy Optimisation
2022 · 16 citations
Structured State Space Models for In-Context Reinforcement Learning
2023 · 11 citations
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading
2023 · 8 citations
Mirror Learning: A Unifying Framework of Policy Optimisation
2022 · 6 citations
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning
2019 · 4 citations
A New Formalism, Method and Open Issues for Zero-Shot Coordination
2021 · 4 citations
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
2024 · 4 citations
Centralized Model and Exploration Policy for Multi-Agent RL
2021 · 3 citations
Grounding Aleatoric Uncertainty for Unsupervised Environment Design
2022 · 3 citations
Top co-authors
Shimon Whiteson
· 9
Chris Lu
· 7
Gregory Farquhar
· 6
Christian Schroeder de Witt
· 5
Michael Dennis
· 5
Mikayel Samvelyan
· 4
Minqi Jiang
· 4
Timon Willi
· 4
Jack Parker-Holder
· 3
Michael Beukman
· 3
Tim Rockt\"aschel
· 3
Alistair Letcher
· 2
Topics
Multi-Agent
Model-Based RL
Game AI
Meta-RL
Policy Gradient
Exploration
Value-Based
Safe RL
Offline RL