2 Ships, 1 Decision: DED-lite Missile Defense in VisualSim | Hackathon 2026

2 warships defend 1 asset against a ballistic missile raid. The question that decides everything is not how fast the missiles fly - it is WHO SHOOTS WHICH THREAT. This 5-min demo presents our VisualSim Hackathon 2026 Challenge 1 entry: a 2-ship DED-lite discrete-event kill-chain model in VisualSim Architect (MissileDefense_Model.xml, about 23 blocks). DED-lite is a minimal, simulatable reduction of the Navy Distributed Engagement Decision (DED) bidded scheme from Moskowitz, Gassler, Paulhamus 2002 (JHU APL Tech Digest 23) to 3 of its 8 sieving tests: capability plus inventory plus load and time-of-flight tie-break, running on a file-backed FES table (fes_table.csv) plus CommonRule plus PolicyRouter. One switch, same raid - 3 doctrines: Policy 0 Sectered (static partition, no comms) | Policy 1 First-Launch (Ship-1 takes all) | Policy 2 DED-lite Bidded (table plus inventory-aware plus shoot-look-shoot re-engagement) Live in video: open model fresh, set Policy_Mode to 2, press GO (stopTime 15s, about 7 threats), check DefenseOutcome plus KillCount plus MissCount (Kills plus Misses equals threats). Evidence: 3-run Pk baseline plus 9-run Policy by Pk sweep plus 90-run Policy by Pk by seeds 2001 to 2010 plus Force_Ship2 proving run. Finding: Mode 1 loses (Ship2 idle, queue plus magazine saturation), Modes 0 and 2 close, Mode 2 edges ahead at high Pk. Key lesson: raw Pk vs effective (on-time, with missile available) Pk - a won dice that arrives late past the 4.0s deadline is still a leaker. Model flow: ThreatGenerator then Detection then FES_DB and Magazine_DB then CommonRule then PolicyRouter then Ship1 and Ship2 Queue then C2 (0.05 to 0.2s) then Flyout (2.0s vs 2.18s) then Kill (Bernoulli Pk, live 10-round magazines, 10 to 30s reload, 2nd attempt if time remains) then Merge then Outcome, Counter, Plotter. All numbers are logical-time simulation outputs driven by assumption-tagged inputs. No classified or measured system data. Based only on public literature. Built with: VisualSim Architect (DEDirector, DS_Source, Expression_Decision, Smart_Resource, DLY, Database, Counter_Basic) plus bat sweeps plus Python scorers.