[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-70777":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":27,"readmeContent":28,"aiSummary":29,"trendingCount":16,"starSnapshotCount":16,"syncStatus":30,"lastSyncTime":31,"discoverSource":32},70777,"spinningup","openai\u002Fspinningup","openai","An educational resource to help anyone learn deep reinforcement learning.","https:\u002F\u002Fspinningup.openai.com\u002F",null,"Python",11806,2453,231,180,0,7,9,42,21,92.7,"MIT License",false,"master",true,[],"2026-06-12 04:00:57","**Status:** Maintenance (expect bug fixes and minor updates)\n\nWelcome to Spinning Up in Deep RL! \n==================================\n\nThis is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL).\n\nFor the unfamiliar: [reinforcement learning](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FReinforcement_learning) (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with [deep learning](http:\u002F\u002Fufldl.stanford.edu\u002Ftutorial\u002F).\n\nThis module contains a variety of helpful resources, including:\n\n- a short [introduction](https:\u002F\u002Fspinningup.openai.com\u002Fen\u002Flatest\u002Fspinningup\u002Frl_intro.html) to RL terminology, kinds of algorithms, and basic theory,\n- an [essay](https:\u002F\u002Fspinningup.openai.com\u002Fen\u002Flatest\u002Fspinningup\u002Fspinningup.html) about how to grow into an RL research role,\n- a [curated list](https:\u002F\u002Fspinningup.openai.com\u002Fen\u002Flatest\u002Fspinningup\u002Fkeypapers.html) of important papers organized by topic,\n- a well-documented [code repo](https:\u002F\u002Fgithub.com\u002Fopenai\u002Fspinningup) of short, standalone implementations of key algorithms,\n- and a few [exercises](https:\u002F\u002Fspinningup.openai.com\u002Fen\u002Flatest\u002Fspinningup\u002Fexercises.html) to serve as warm-ups.\n\nGet started at [spinningup.openai.com](https:\u002F\u002Fspinningup.openai.com)!\n\n\nCiting Spinning Up\n------------------\n\nIf you reference or use Spinning Up in your research, please cite:\n\n```\n@article{SpinningUp2018,\n    author = {Achiam, Joshua},\n    title = {{Spinning Up in Deep Reinforcement Learning}},\n    year = {2018}\n}\n```","Spinning Up 是一个由 OpenAI 提供的教育资源，旨在帮助人们学习深度强化学习。该项目以 Python 语言编写，提供了丰富的学习资料，包括强化学习的基础理论介绍、关键算法的实现代码以及相关论文列表等。其核心功能在于通过简洁且独立的代码示例和详尽文档来降低初学者的学习门槛，并为希望深入研究该领域的用户提供指导。适合任何对深度强化学习感兴趣并希望系统性地掌握相关知识和技术的研究者、开发者或学生使用。",2,"2026-06-11 03:34:07","high_star"]