research
∙
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...
share
research
∙
06/23/2022
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos
Pretraining on noisy, internet-scale datasets has been heavily studied a...
research
∙
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...
research
∙
06/28/2021
Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft
An important challenge in reinforcement learning is training agents that...
research
∙
06/07/2021
Towards robust and domain agnostic reinforcement learning competitions
Reinforcement learning competitions have formed the basis for standard r...
research
∙
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...
research
∙
05/12/2020
Guaranteeing Reproducibility in Deep Learning Competitions
To encourage the development of methods with reproducible and robust tra...
research
∙
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...
research
∙
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...
research
∙
07/29/2019
MineRL: A Large-Scale Dataset of Minecraft Demonstrations
The sample inefficiency of standard deep reinforcement learning methods ...
research
∙
04/22/2019
