WebWe introduce a simple and effective method for learning VAEs with controllable inductive biases by using an intermediary set of latent variables. This allows us to overcome the limitations of the... WebMultitask Soft Option Learning ‣ Abstract Igl, M., Gambardella, A., He, J., Nardelli, N., Siddharth, N., Böhmer, W., & Whiteson, S. arXiv We combine ideas from Planning as Inference and hierarchical latent variable models to …
Learning Task Sampling Policy for Multitask Learning
Web25 sept. 2024 · MSOL extends the concept of Options, using separate variational posteriors for each task, regularized by a shared prior. The learned soft-options are temporally … http://proceedings.mlr.press/v124/igl20a.html popeyes gulf breeze
Multi-task & Meta-learning basics by Qiurui Chen Medium
Web6 dec. 2024 · Although option learning was initially formulated in a way that allows updating many options simultaneously, using off-policy, intra-option learning (Sutton, Precup Singh, 1999), many of the recent hierarchical reinforcement learning approaches only update a single option at a time: the option currently executing. Web1 apr. 2024 · Multitask Soft Option Learning. We present Multitask Soft Option Learning (MSOL), a hierarchical multitask framework based on Planning as Inference. MSOL … Web27 aug. 2024 · We present Multitask Soft Option Learning (MSOL), a hierarchical multitask framework based on Planning as Inference. MSOL extends the concept of … share price qa