mlsanityData to 7 Oct 2026

JaxUED: A simple and useable UED library in Jax

arXiv 2403.13091 ↗First posted 19 Mar 2024cs.LG cs.AIcited by 10

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Abstract (arXiv)

We present JaxUED, an open-source library providing minimal dependency implementations of modern Unsupervised Environment Design (UED) algorithms in Jax. JaxUED leverages hardware acceleration to obtain on the order of 100x speedups compared to prior, CPU-based implementations. Inspired by CleanRL, we provide fast, clear, understandable, and easily modifiable implementations, with the aim of accelerating research into UED. This paper describes our library and contains baseline results. Code can be found at https://github.com/DramaCow/jaxued.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 13 of its 20 references that are in the map. First posted on arXiv 19 Mar 2024.

Builds on

13 of 20 references.

References · 13

  1. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,401
  2. 2017Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithmcited by 723
  3. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 375
  4. 2023Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Taskscited by 320
  5. 2020Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Designcited by 260
  6. 2020Prioritized Level Replaycited by 190
  7. 2022Evolving Curricula with Regret-Based Environment Designcited by 166
  8. 2023Human-Timescale Adaptation in an Open-Ended Task Spacecited by 136
  9. 2021Replay-Guided Adversarial Environment Designcited by 108
  10. 2022Discovered Policy Optimisationcited by 103
  11. 2023Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learningcited by 45
  12. 2023Stabilizing Unsupervised Environment Design with a Learned Adversarycited by 17
1 more
  1. 2023minimax: Efficient Baselines for Autocurricula in JAXcited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 2; 2026: 4.

10 papers.

  1. 2024Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Taskscited by 40
  2. 2024No Regrets: Investigating and Improving Regret Approximations for Curriculum Discoverycited by 29
  3. 2024The Overcooked Generalisation Challenge: Evaluating Cooperation with Novel Partners in Unknown Environments Using Unsupervised Environment Designcited by 11
  4. 2024Syllabus: Portable Curricula for Reinforcement Learning Agentscited by 2
  5. 2025gfnx: Fast and Scalable Library for Generative Flow Networks in JAXcited by 2
  6. 2025Video Game Level Design as a Multi-Agent Reinforcement Learning Problemcited by 1
  7. 2026Improving Regret Approximation for Unsupervised Dynamic Environment Generationcited by 1
  8. 2026TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learningcited by 0
  9. 2026NASimJax: A GPU-Accelerated Policy Learning Framework for Penetration Testingcited by 0
  10. 2026Jaxolotl: A Unified High-Performance Benchmark Suite for LTL-Based Multi-Task RLcited by 0