Among LLMs is a game-like OpenEnv benchmark where attacker, defender, and overseer agents interact in sabotage-style workplace tasks. It starts with deterministic, replayable episodes and reward signals, then scales into self-evolving multi-agent curricula through mutation, archival failures, and harder rollouts. The goal is to train robust oversight that detects manipulation, localizes root causes, and improves continuously via self-play-style adaptation
Kube SRE Gym is a self-improving RL environment where a small language model (Qwen3-1.7B) learns to diagnose and fix real Kubernetes production incidents…
RL environment for autonomous biologist agents. Simulate an entire biological worldstate based on scientifically-accurate single-cell standards. Naive agents…
ShopRLVE-GYM HF Blog https://huggingface.co/blog/thebajajra/shop-rlve-gym
Our agent uses OpenEnv to build a curriculum of video game environments that train a TinyLlama 1.1B agent via GRPO reinforcement learning. We implement three…
GAIA is an OpenEnv-compatible geospatial reasoning environment where an AI agent infers hidden real-world locations using multi-step tool calls (terrain…
Voyager-VRAM is a long-horizon workplace simulator where LLM agents must navigate a realistic office environment ( emails, Slack, shared drive, spreadsheets…
