# Garden RL - Lettuce Win

- **Event:** [OpenEnv Hackathon SF](https://cerebralvalley.ai/e/openenv-hackathon-sf)
- **When:** Mar 7 at 9:00 AM – Mar 8 at 12:00 AM (PST)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Yves Hughes](https://cerebralvalley.ai/u/yvesjr)
- **Website:** https://colab.research.google.com/drive/1_RmjDUtdpki6KJHuqGqElWMn3X5nOhx7?usp=sharing
- **Demo video:** https://us06web.zoom.us/clips/share/6cvGbWGoTXWsAH5RLJm_fw
- **Hugging Face:** https://huggingface.co/spaces/yvesjr/GardenRL
- **Gallery:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/42

GardenRL teaches AI agents to grow hydroponic lettuce through 30-day episodes with delayed rewards. A pH mistake on day 5 causes calcium lockout, brown leaf tips by day 9, and 60% yield loss by day 30 — requiring genuine long-horizon planning and hidden-state inference.

Grounded in the HydroGrowNet dataset (390K real images), rewards are verifiable harvest weight in grams — no LLM judge. We trained Llama-3.1-8B with GRPO (OpenPipe ART) for 50 steps: reward +473%, eval harvest +11%, success rate 50%→60% on held-out seeds.

Addresses Problem Statement 2 (Long-Horizon Planning) and 3.1 (World Modeling) and the Mercor sub-bounty.

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Markdown version of https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/42. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt