AI Augmented
Mutating Ontologies
in Fractal Narratives
Exploring the application of Large Language Models (LLMs) to dynamically restructure narrative frameworks in real-time. This research proposes a system where the "world model" (ontology) mutates based on observer interaction, allowing for stories with infinite recursive depth.
Mutating Ontology
A knowledge graph that rewrites its own schema. New entities and relationships are born from user focus, rather than pre-defined databases.
Fractal Structure
Narrative recursion. Just as a coastline reveals more detail as you zoom in, the story generates new plots within plots indefinitely.
The Loop
User Interaction → Context Analysis → Ontology Mutation → Content Generation. A feedback loop creating the illusion of a living world.
Dynamic Semantic Space
This visualization represents the "current active ontology" of a narrative. Each bubble is a narrative entity. Click any node to trigger a "Mutation Event." The system will re-center on that concept and generate sub-ontologies (fractal zoom).
Current State Analysis
System initialized. Root ontology loaded. Awaiting user focus input to determine mutation vector.
Active Entities
The Fractal Engine Prototype
Experience the concept directly. Below is a seed text. Click the highlighted terms to observe how the ontology mutates to generate context-specific, recursive narrative layers on the fly.
The Traveler stood at the edge of the Void, holding the Artifact. It hummed with a resonance that seemed to predate the stars themselves.
Mutation Log
Parameters
System Analysis & Architecture
Evaluating the theoretical performance and structural requirements of an AI-driven recursive narrative system.
The Mutation Loop Architecture
Coherence Decay Analysis
As recursive depth (fractal zoom) increases, narrative coherence typically degrades without strict ontology anchoring.
Entity Generation Rate
Computational cost and unique entities generated scale exponentially with each narrative branch depth.