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03/06/2023
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning
Open-ended learning methods that automatically generate a curriculum of ...
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12/14/2022
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
The availability of challenging benchmarks has played a key role in the ...
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07/23/2022
Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning
Practising and honing skills forms a fundamental component of how humans...
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07/13/2022
GriddlyJS: A Web IDE for Reinforcement Learning
Progress in reinforcement learning (RL) research is often driven by the ...
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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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03/02/2022
Evolving Curricula with Regret-Based Environment Design
It remains a significant challenge to train generally capable agents wit...
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10/27/2021
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions
We present an extended abstract for the previously published work TESSER...
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09/27/2021
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
The progress in deep reinforcement learning (RL) is heavily driven by th...
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05/31/2021
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Reinforcement Learning in large action spaces is a challenging problem. ...
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03/19/2020
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
In many real-world settings, a team of agents must coordinate its behavi...
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10/16/2019
MAVEN: Multi-Agent Variational Exploration
Centralised training with decentralised execution is an important settin...
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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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03/30/2018
