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03/22/2022
Insights From the NeurIPS 2021 NetHack Challenge
In this report, we summarize the takeaways from the first NeurIPS 2021 N...
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07/17/2020
WordCraft: An Environment for Benchmarking Commonsense Agents
The ability to quickly solve a wide range of real-world tasks requires a...
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06/24/2020
The NetHack Learning Environment
Progress in Reinforcement Learning (RL) algorithms goes hand-in-hand wit...
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05/14/2020
Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidem...
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12/13/2019
Lessons from reinforcement learning for biological representations of space
Neuroscientists postulate 3D representations in the brain in a variety o...
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10/09/2019
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions
Effective network congestion control strategies are key to keeping the I...
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10/08/2019
TorchBeast: A PyTorch Platform for Distributed RL
TorchBeast is a platform for reinforcement learning (RL) research in PyT...
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06/10/2019
A Survey of Reinforcement Learning Informed by Natural Language
To be successful in real-world tasks, Reinforcement Learning (RL) needs ...
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04/01/2019
Multitask Soft Option Learning
We present Multitask Soft Option Learning (MSOL), a hierarchical multita...
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02/11/2019
The StarCraft Multi-Agent Challenge
In the last few years, deep multi-agent reinforcement learning (RL) has ...
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05/28/2018
Value Propagation Networks
We present Value Propagation (VProp), a parameter-efficient differentiab...
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05/24/2017
Counterfactual Multi-Agent Policy Gradients
Cooperative multi-agent systems can be naturally used to model many real...
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02/28/2017
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Many real-world problems, such as network packet routing and urban traff...
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12/01/2016
Playing Doom with SLAM-Augmented Deep Reinforcement Learning
A number of recent approaches to policy learning in 2D game domains have...
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11/01/2016
