Implicit Curriculum in Procgen Made Explicit

Zhenxiong Tan, Kaixin Wang, Xinchao Wang
2/3/2026

No confident code implementation found for this paper. 1 possible match can be shown below.

Abstract

Procedurally generated environments such as Procgen Benchmark provide a testbed for evaluating the agent’s ability to robustly learn a relevant skill, by situating the agent in ever-changing levels. The diverse levels associated with varying contexts are naturally connected to curriculum learning. Existing works mainly focus on arranging the levels to explicitly form a curriculum. In this work, we take a close look at the learning process itself under the multi-level training in Procgen. Interestingly, the learning process exhibits a gradual shift from easy contexts to hard contexts, suggesting an implicit curriculum in multi-level training. Our analysis is made possible through C-Procgen , a benchmark we build upon Procgen that enables explicit control of the contexts. We believe our findings will foster a deeper understanding of learning in diverse contexts, and our benchmark will benefit future research in curriculum reinforcement learning.

DOISemantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{tan2026implicit,
  title  = {Implicit Curriculum in Procgen Made Explicit},
  author = {Zhenxiong Tan and Kaixin Wang and Xinchao Wang},
  year   = {2026},
  doi    = {10.52202/079017-0646},
  url    = {https://doi.org/10.52202/079017-0646},
  journal = {NEURIPS 2024 2024}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/56b23122a08066f63b3998209a2da5492a04fb94.svg)](https://codeofpaper.com/paper/56b23122a08066f63b3998209a2da5492a04fb94)

Discussion