Research map / Learning theory and algorithms / Submodular and game algorithms
To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| model detection uncertainty instead of ignoring it (ablation) | GUARDSS · Detection uncertainty gamma 0 to 0.9 | defender expected utility decrease: 210% -> 12% decrease | Helped |
| model observational uncertainty instead of ignoring it (ablation) | GUARDSS · Observational uncertainty kappa 0 to 0.9 | defender expected utility decrease: 18% -> 1% decrease | Helped |
| replace sensor-based drones with extra patroller at low detection uncertainty | GUARDSS · Simulation N=15 | defender expected utility: drones better at gamma 0.3, patrollers better at gamma 0.8 | Mixed |
| add warm-up greedy initial set to branch and price | GUARDSS · Scalability N=90,100 | graphs solved in time: 13/40 solved | Helped |
| use drones with GUARDSS vs forgoing drones or ignoring uncertainty | GUARDSS · Conservation park case study | defender expected utility | Helped |
| heuristics vs full LP | GUARDSS heuristics · Random graphs | solution quality | No clear effect |
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