--- title: Safety Gym | daily.dev description: OpenAI released Safety Gym, a benchmark suite of environments and tools for evaluating reinforcement learning agents that respect safety constraints during... canonical: https://daily.dev/posts/safety-gym-8humb4vql twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Safety Gym | daily.dev og:description: OpenAI released Safety Gym, a benchmark suite of environments and tools for evaluating reinforcement learning agents that respect safety constraints during... og:url: https://daily.dev/posts/safety-gym-8humb4vql og:image: https://api.daily.dev/og/posts/8HUmB4vQl.png og:image:alt: Safety Gym og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Safety Gym **[OpenAI](https://daily.dev/sources/openai)** · 8 min read · 0 upvotes · 0 comments ## Summary OpenAI released Safety Gym, a benchmark suite of environments and tools for evaluating reinforcement learning agents that respect safety constraints during training. The release addresses the 'safe exploration' problem — where RL agents may take dangerous actions while learning — by adopting constrained RL as a formalism. Unlike standard RL where safety trade-offs are baked into a fixed reward function, constrained RL lets developers specify acceptable outcome thresholds (e.g., collision rates) and lets algorithms find the right trade-offs automatically. Safety Gym includes three robots (Point, Car, Doggo), three task types (Goal, Button, Push), and two difficulty levels. Baseline evaluations of PPO, TRPO, and Constrained Policy Optimization (CPO) are provided, with a notable finding that Lagrangian methods outperformed CPO. Code for Safety Starter Agents is also released to support reproducibility and future research. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [AI Agent Benchmark: New Safety Standards Revealed](https://daily.dev/posts/ai-agent-benchmark-new-safety-standards-revealed-crdplyvjd) · IEEE Spectrum · 0 upvotes · 0 comments - [MCP Moment for Reinforcement Learning](https://daily.dev/posts/mcp-moment-for-reinforcement-learning-dgav6ydga) · Daily Dose of Data Science \| Avi Chawla \| Substack · 1 upvotes · 0 comments - [New control system teaches soft robots the art of staying safe](https://daily.dev/posts/new-control-system-teaches-soft-robots-the-art-of-staying-safe-djqgrylwp) · MIT News · 0 upvotes · 0 comments --- Tags: [#openai](https://daily.dev/tags/openai), [#robotics](https://daily.dev/tags/robotics), [#reinforcement-learning](https://daily.dev/tags/reinforcement-learning) [View this post on daily.dev](https://daily.dev/posts/safety-gym-8humb4vql) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Safety Gym","url":"https://daily.dev/posts/safety-gym-8humb4vql","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/safety-gym-8humb4vql"},"datePublished":"2026-07-09T18:39:06.843Z","dateModified":"2026-07-09T19:27:40.138Z","description":"OpenAI released Safety Gym, a benchmark suite of environments and tools for evaluating reinforcement learning agents that respect safety constraints during...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/92526fbf0d43f7157bd9558ad5e54451?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/92526fbf0d43f7157bd9558ad5e54451?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"OpenAI","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"OpenAI","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/984b3632316f4afaa3d5213d5c64fe65","url":"https://daily.dev/sources/openai"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/safety-gym-8humb4vql","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"openai,robotics,reinforcement-learning","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"OpenAI","item":"https://daily.dev/sources/openai"},{"@type":"ListItem","position":3,"name":"Safety Gym"}]} ```