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Agent-based dashboard: how a deepfake spreads through a school network, and where a limited education budget actually helps. Illustrative, not validated.
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Justin Visser 33d40a18ea engine: seeded RNG helper, first tests 
math/rand/v2 (Go 1.22+) replaces the old math/rand: PCG generator,
no global Seed(), and rand.New(rand.NewPCG(seed, 0)) gives an isolated
deterministic stream. Each randomness consumer (graph, thresholds,
education sampling) will get its own stream so levers vary independently.
Tests live next to the code as *_test.go; 'go test ./...' runs them all.
'for i := range 100' is Go 1.22 range-over-int.
2026-06-10 11:57:39 +02:00
cmd/spreadlab batman 2026-06-10 11:57:10 +02:00
internal/engine engine: seeded RNG helper, first tests 2026-06-10 11:57:39 +02:00
.gitignore batman 2026-06-10 11:57:10 +02:00
go.mod batman 2026-06-10 11:57:10 +02:00
LICENSE batman 2026-06-10 11:57:10 +02:00
README.md batman 2026-06-10 11:57:10 +02:00

README.md

spreadlab

Self-hosted dashboard that runs an agent-based deepfake-spread model live: change the levers, watch the spread, and (later) search for the best intervention under a budget. Output is illustrative, not validated.

Status: milestone 1, porting the simulation engine.

Layout:

  • internal/engine/ - the pure simulation engine (no web dependencies)
  • cmd/spreadlab/ - the server binary (milestone 2)
  • web/ - Vue 3 + TypeScript frontend (milestone 2+)

MIT licensed.