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0b2675d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | # Citation
If you use 911 Dispatch Supervisor in your research, please cite:
```bibtex
@software{dispatch_supervisor_2025,
title = {911 Dispatch Supervisor: An Open RL Benchmark for Emergency Dispatch Decision-Making},
year = {2025},
url = {https://huggingface.co/spaces/garvitsachdeva/911},
note = {OpenEnv-compatible environment for training and evaluating LLM agents
on real-world emergency resource allocation under time pressure}
}
```
## Research Applications
This environment is designed to support research in:
- LLM decision-making under constraint — fixed action budgets, time pressure
- Multi-objective RL — non-sparse rewards with competing components
- AI safety evaluation — hard constraints (Safety Gate) that cannot be gamed
- Human-AI collaboration — dispatch copilot systems for public safety
## Dataset & Reproducibility
All episodes are fully deterministic under seed=42. The random agent baseline
produces identical scores on every run, enabling valid cross-environment comparisons.
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