# mtrxk (Solo)

- **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:** [Harish Chaurasia](https://cerebralvalley.ai/u/harishchaurasia)
- **GitHub:** https://github.com/harishchaurasia/Meta_OpenEnv_PyTorch_Hack
- **Website:** https://colab.research.google.com/drive/1955RHZoX_68Ra-HhZqJJy5VZPCqOgSN_?usp=sharing
- **Demo video:** https://youtu.be/SisAhzK3_Ow
- **Hugging Face:** https://huggingface.co/spaces/harishchaurasia/adaptive-nav-openenv
- **Gallery:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/18

Adaptive Navigation OpenEnv is a partially observable exploration environment designed for training and evaluating LLM agents on multi-step planning tasks. The agent operates in a 2D world where it only sees a small local observation window and must navigate efficiently under energy constraints.

The objective is to collect a key, unlock a checkpoint, and reach a goal while reasoning over incomplete information. The environment includes dynamic obstacles, mission tracking, and reward feedback, making it suitable for reinforcement learning and agentic decision-making research.

The project demonstrates a full pipeline including an interactive Streamlit environment, OpenEnv deployment on Hugging Face Spaces, and a minimal HF TRL training scaffold in Colab. This environment provides a compact benchmark for studying autonomous exploration, navigation, and planning with language model agents.

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Markdown version of https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/18. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt