English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Unsupervised environment design (UED) is a form of automatic curriculumlearning for training robust decision-making agents to zero-shot transfer intounseen environments. Such autocurricula have received much interest from the RLcommunity. However, UED experiments, based on CPU rollouts and GPU modelupdates, have often required several weeks of training. This computerequirement is a major obstacle to rapid innovation for the field. This workintroduces the minimax library for UED training on accelerated hardware. UsingJAX to implement fully-tensorized environments and autocurriculum algorithms,minimax allows the entire training loop to be compiled for hardwareacceleration. To provide a petri dish for rapid experimentation, minimaxincludes a tensorized grid-world based on MiniGrid, in addition to reusableabstractions for conducting autocurricula in procedurally-generatedenvironments. With these components, minimax provides strong UED baselines,including new parallelized variants, which achieve over 120$\times$ speedups inwall time compared to previous implementations when training with equal batchsizes. The minimax library is available under the Apache 2.0 license athttps://github.com/facebookresearch/minimax.

minimax: Efficient Baselines for Autocurricula in JAX