# Ludus Magnus

- **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:** [Harshit Rajgarhia](https://cerebralvalley.ai/u/hrajgarhia), [Abhishek Mukherji](https://cerebralvalley.ai/u/mukherjiab), [Karl Johannes](https://cerebralvalley.ai/u/KarlLearnsAI)
- **GitHub:** https://github.com/KarlLearnsAI/nested-rl-envs
- **Website:** https://huggingface.co/spaces/openenv-community/test-local-nested-envs/blob/main/minimum_training_script.ipynb
- **Demo video:** https://youtu.be/wZ96i4gk9t8
- **Hugging Face:** https://huggingface.co/spaces/openenv-community/test-local-nested-envs
- **Gallery:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/41

RL-IVR is a three-layered RL environment that trains voice agents to replace legacy IVR systems. We stress-test our voice agents with simulated customer-agent interactions, and a GRPO training loop evolves the agent from generic to surgical, learning on its own to detect intent and resolve queries in fewer turns. Domain-aware adaptive reward modeling enables the same architecture to generalize across banking, healthcare, and telecom without any manual reward re-engineering.

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Markdown version of https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/41. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt