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04/12/2023
Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning
Despite their potential in real-world applications, multi-agent reinforc...
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03/23/2023
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition
To facilitate research in the direction of fine-tuning foundation models...
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03/02/2023
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games
We aim to understand how people assess human likeness in navigation prod...
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11/20/2022
UniMASK: Unified Inference in Sequential Decision Problems
Randomly masking and predicting word tokens has been a successful approa...
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05/25/2022
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
Many recent breakthroughs in multi-agent reinforcement learning (MARL) r...
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04/28/2022
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers
Randomly masking and predicting word tokens has been a successful approa...
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04/14/2022
Retrospective on the 2021 BASALT Competition on Learning from Human Feedback
We held the first-ever MineRL Benchmark for Agents that Solve Almost-Lif...
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02/17/2022
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned
Reinforcement learning competitions advance the field by providing appro...
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02/17/2022
A Survey of Explainable Reinforcement Learning
Explainable reinforcement learning (XRL) is an emerging subfield of expl...
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07/05/2021
The MineRL BASALT Competition on Learning from Human Feedback
The last decade has seen a significant increase of interest in deep lear...
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06/07/2021
Towards robust and domain agnostic reinforcement learning competitions
Reinforcement learning competitions have formed the basis for standard r...
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02/25/2021
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods
Current work in explainable reinforcement learning generally produces po...
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01/26/2021
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
Although deep reinforcement learning has led to breakthroughs in many di...
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05/12/2020
Guaranteeing Reproducibility in Deep Learning Competitions
To encourage the development of methods with reproducible and robust tra...
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03/10/2020
The MineRL Competition on Sample-Efficient Reinforcement Learning Using Human Priors: A Retrospective
To facilitate research in the direction of sample-efficient reinforcemen...
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03/10/2020
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning
To facilitate research in the direction of sample-efficient reinforcemen...
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12/16/2019
Planning with Abstract Learned Models While Learning Transferable Subtasks
We introduce an algorithm for model-based hierarchical reinforcement lea...
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04/22/2019
