Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition

no code implementations • 23 Mar 2023 • Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen Novoseller, Vinicius G. Goecks, Nicholas Waytowich, David Watkins, Josh Miller, Rohin Shah

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 2022.

Improving performance in multi-objective decision-making in Bottles environments with soft maximin approaches

no code implementations • 8 Aug 2022 • Benjamin J Smith, Robert Klassert, Roland Pihlakas

Due to publishing rules, further work could not be presented in the preprint, but in the final published version, we will further compare SFELLA to the multi-objective reward exponentials (MORE) approach (Rolf, 2020), demonstrating that SFELLA performs similarly to MORE in a simple previously-described foraging task, but in a modified foraging environment with a new resource that was not depleted as the agent worked, SFELLA collected more of the new resource with very little cost incurred in terms of the old resource.

Decision Making

Variational learning of quantum ground states on spiking neuromorphic hardware

no code implementations • 30 Sep 2021 • Robert Klassert, Andreas Baumbach, Mihai A. Petrovici, Martin Gärttner

Recent research has demonstrated the usefulness of neural networks as variational ansatz functions for quantum many-body states.