Bayesian Optimization Engine Mechanics — DEJAN Codebase Explorer

The engine generates hypotheses for content improvement, applies them via an ideator model, re-ranks candidate drafts against live search results, and updates posterior probabilities to iteratively converge on winning edits.

sequenceDiagram
    autonumber
    participant S as Seeder / Ideator
    participant R as Ranker / Judge
    participant B as Bayesian Engine (Posterior)
    S->>R: Propose snippet / page edit
    R->>R: Rank draft against competitors
    R->>B: Observe rank outcome (Reward 0 or 1)
    B->>B: Update Beta(alpha, beta) distribution
    B->>S: Select highest-potential claim (Thompson/UCB)

Referenced by

Content Optimizer Mechanism