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| # 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 β fixed action budgets, time pressure | |
| - Multi-objective RL β non-sparse rewards with competing components | |
| - AI safety evaluation β hard constraints (Safety Gate) that cannot be gamed | |
| - Human-AI collaboration β 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. | |