Heterogeneous fleet comparison across static basing, random patrol, and task-aware patrol under changing mission demand.
Generated from analysis.duckdb. The top-ranked policy is highlighted below.
Sorted by mission-fit score. Scroll horizontally if your viewport is narrow.
| strategy | mission_fit_score | final_weighted_coverage | avg_task_service_rate | task_completion_rate | mean_task_response_time | coverage_efficiency |
|---|---|---|---|---|---|---|
| priority_patrol | 0.680 | 0.562 | 0.384 | 1.000 | 2.150 | 0.000 |
| greedy_patrol | 0.620 | 0.496 | 0.381 | 0.750 | 2.467 | 0.000 |
| patrol | 0.516 | 0.834 | 0.086 | 0.850 | 6.500 | 0.001 |
| static | 0.491 | 0.107 | 0.106 | 0.750 | 0.000 | 0.000 |
The same outputs feed BI, notebooks, and lightweight ETL.
Each run writes one DuckDB file plus one Parquet file per logical table. That makes downstream consumption (notebooks, dashboards, sweep aggregation jobs) the same shape as a tiny analytics warehouse instead of a folder of CSVs.
Regenerated on every run; the same files back the live-demo gallery.
