Function updateAdaptiveWeights

updateAdaptiveWeights(
    reward: number,
    breakdown: Record<string, ScorerBreakdown>,
    optionsOrLearningRate?: number | AdaptiveWeightUpdateOptions,
): void
Applies one online gradient step to the globally learned weights.
```
Δweight = learningRate × reward × contribution
```
Scorers with high contribution to a good outcome get heavier; scorers that pushed a bad decision get lighter. The update is idempotent with respect to sign: a series of failures will keep driving a weight toward WEIGHT_MIN but can never push it below that floor.

NaN and zero rewards are ignored (no-ops).
Parameters
- reward: number
  Continuous reward signal in [−1, 1]; from correlateOutcome.
- breakdown: Record<string, ScorerBreakdown>
  Per-scorer contributions from the decision being evaluated.
- optionsOrLearningRate: number | AdaptiveWeightUpdateOptions = LEARNING_RATE
  Either a legacy numeric learning rate, or an options object with namespace and/or learningRate.
Returns void
- Defined in kernel/adaptiveWeights.ts:366