评估与改进智能体的框架
rl-environments 开源项目推荐(68 个)
rl-environments 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 68 个仓库一个精心策划的非BS图书馆,包含构建和评估人工智能代理的最佳资源--论文、博客、讲座、工具、基准。由BenchFlow维护。
Turn any repository into verifiable RL environments for coding agents - Harbor tasks you can train on, evaluate and share on the Hugging Face Hub
FineEnvs — RL Environments 101: building and scaling RL environments in the age of LLMs
A Universal Platform for Training and Evaluation of Mobile Interaction
A graphical interface for reinforcement learning and gym-based environments.
RL environments with verifiable rewards you can trust. Sandboxed coding and computer-use tasks, verifiers kept apart from the answer, a QA gate against reward hacking, and infra failures kept out of training. Works with verl, TRL, OpenRLHF and Axolotl.
Interoperating between (Deep) Reiforcement Learning libraries
Gymnasium-style API standard for RL environment creation in JAX
Workspace manager for coding agents. Interactively solve and develop Harbor tasks.
Awesome Environment Scaling for AI Agents — a periodically updated survey and curated list of papers, projects, RL environments, world models, agent sandboxes, and open research problems
An agentic auditor for RL environments and eval suites. Emits an Environment Card: every claim tied to a probe result, and every probe that could not run, with the reason.
Create new gridworld gym environments easily
Turn any real software into a replayable RL environment for training AI agents — deterministic replay, verifiable rewards, TRL & verifiers adapters.
A curated list of environments, benchmarks, datasets, and RL training resources for workplace AI agents: email, chat, calendar, docs, and enterprise apps.
Check the checker: an open standard for testing the graders of RL environments, with proof before every accusation.
Deterministic, auto-graded environments for AI agents on Indian-reality tasks: UPI, GST, trip planning, forms, Hindi/Hinglish support. Rule-based grading, no LLM judge.
Simulating Backend APIs for RL environments
Independent exact certification of machine-generated mathematics — exact arithmetic, no code shared with the claimant, refusal as a verdict.
Adversarial QA for LLM-RL environments: find out what reward an empty answer earns. Model-free, zero API cost.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/rl-environments。
- 该话题在 GitHub 上共有 68 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 9376 Star,覆盖 2 种主要语言,数据更新于 2026-11-06。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。