87 citations · 170 across the 26 of their papers we have counts for
4 papers · 1 filter
BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks
Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas +3
The MineRL BASALT competition has served to catalyze advances in learning from human feedback through four hard-to-specify tasks in Minecraft, such as create and photograph a water…
Visual Encoders for Data-Efficient Imitation Learning in Modern Video Games
Lukas Schäfer, Logan Jones, Anssi Kanervisto +7
Video games have served as useful benchmarks for the decision-making community, but going beyond Atari games towards modern games has been prohibitively expensive for the vast majo…
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition
Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas +27
To facilitate research in the direction of fine-tuning foundation models from human feedback, we held the MineRL BASALT Competition on Fine-Tuning from Human Feedback at NeurIPS 20…
Imitating Human Behaviour with Diffusion Models
Tim Pearce, Tabish Rashid, Anssi Kanervisto +8
Diffusion models have emerged as powerful generative models in the text-to-image domain. This paper studies their application as observation-to-action models for imitating human be…