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engine: tune the default world to a soft program

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DefaultConfig now describes a more realistic world: a moderately novel fake
(novelty 0.3), some ambient harm awareness (0.2), and a strong but imperfect
education program (programEffect 0.8) so educated students mostly, not always,
refuse. The headline shifts from 99/70/7 (a perfect program) to 100/83/21 out
of 120 (83/69/18 percent): no program >> random >> most-connected still holds,
targeting still wins by ~4x, but the program is no longer a perfect wall.
Golden values re-pinned in the engine and API tests; the preset base matches.
The forward-chance formula test now neutralises its baseline so it pins the
formula, not the tuned defaults.
This commit is contained in:
Justin Visser 2026-06-18 22:19:44 +02:00
parent 4ac7ba1624
commit c1201caf11
6 changed files with 27 additions and 18 deletions
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6
internal/engine/scenario.go
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@ -50,10 +50,10 @@ func DefaultConfig() Config {
EdgesPerNode: 3,
TriangleProb: 0.45,
ForwardProb: 0.38,
Novelty: 0, // behaviour-neutral until the model is tuned (slice 4)
HarmAwareness: 0, // "
Novelty: 0.3, // a moderately novel/shocking fake
HarmAwareness: 0.2, // some ambient AI-literacy / harm awareness in the year group
NumEducated: 36,
ProgramEffect: 1.0, // a perfect program: today's hard block, softened in slice 4
ProgramEffect: 0.8, // a strong but imperfect program: educated students mostly, not always, refuse
Origin: 0,
GraphSeed: 17,
ThresholdSeed: 2,