Crate fabula_narratives

Expand description

Narrative scoring and thread management for fabula.

Provides the GM’s evaluation toolkit — scoring signals that tell the MCTS evaluation function whether a candidate action improves the narrative.

§Research foundation

Nelson & Mateas (2005) “Search-Based Drama Management” (AIIDE 2005) — GM as optimizer with quality function over narrative states. This crate IS that quality function. The scorer module implements the composite evaluation from signals to score.
Schulz et al. (2024) “Narrative Information Theory” (arXiv:2411.12907) — Five measures (Complexity, Pivot, Predictability, Suspense, Plot Twist). pivot implements the Pivot measure via Jensen-Shannon Divergence.
Booth (2009) “The AI Director: Left 4 Dead’s Approach to Procedural Intensity” — Pacing via trajectory sampling. tension classifies numeric trajectories (Rising/Falling/Plateau/Peak/Valley).
Ely, Frankel, Kamenica (2015) “Suspense and Surprise” — Trajectory matters more than absolute value; informs tension scoring.
Kowal, Mary Robinette. MICE Quotient (Writing Excuses) — Narrative threads open and close; well-formed stories close in reverse order (FILO). thread validates this nesting property.

thread — Thread lifecycle management (MICE-style open/close tracking, FILO validation)
tension — Numeric trajectory sampling (is tension rising/falling/plateaued?)
pivot — Event distribution shift detection (Schulz 2024 JSD pivot measure)
scorer — Composite narrative quality score for MCTS evaluation

Scoring, not patterns. The GM needs scoring signals, not more patterns. The engine finds matches; this crate evaluates narrative quality.
DataSource-agnostic where possible. ThreadTracker and PivotDetector work on engine output (TickDelta, SiftEvent). TensionTracker accepts caller-provided samples, not DataSource queries.
Research-backed. Each module cites its academic foundation.