Step 1: Define the Core Ontology of Synthia
The ontology is the conceptual backbone — the types of entities, interactions, and narrative elements that exist in Synthia stories.
Entities in Synthia:
Artifacts – Goal: Create units of meaning triggered by presence. Why first: They teach the world to “speak” in Synthia. Output: Ghost-like traversal, text/audio/symbol feedback. Artifacts are the atoms of Synthia. Everything else is built on them.
Thespians – Characters or AI-driven entities that act and evolve.
Nodes – Story moments or events; discrete units of plot.
Channels – Mediums of expression (visual, auditory, textual, hybrid).
States – Emotional, informational, or existential conditions of Thespians or nodes.
Rules – Constraints that define cause-effect, logic, and world consistency.
Latent Spaces – The AI-interpreted universe of possibilities; “what could happen” rather than “what did happen.”
Core Principles:
Every story is a network of nodes and Thespians, not a linear chain.
Thespians can have partial autonomy, making decisions that generate emergent narratives.
Nodes are indexed semantically, so AI can recombine them across stories or universes.
States are multi-dimensional, allowing characters to exist in overlapping emotional or logical spaces.
Rules are modifiable, letting creators experiment with alternate physics, logic, or causality.
Latent spaces allow AI to predict and generate story continuations based on probabilistic logic, not linear scripts.
Step 2: Story Architecture
A. Narrative Graphs
Stories in Synthia are directed graphs:
Vertices = Nodes (events)
Edges = Causal or thematic links
Weights = Emotional intensity, narrative importance, probability of choice
Graphs are dynamic, evolving with Thespian decisions.
Example: Node A (Thespian meets Mentor) → Node B (Conflict arises) → Node C (AI generates 3 possible endings)
B. Multi-Layered Perspective
Every story has 3 layers of perception:
Human-perceived layer: How a human reads/watches the story.
Thespian-perceived layer: AI simulates Thespian goals, emotions, and biases.
Meta-layer: AI observes global story trends, emergent patterns, and latent possibilities.
C. Narrative Primitives
Archetypes: Basic Thespian types (Hero, Guide, Antagonist, Observer)
Plot Motifs: Small reusable story patterns (Conflict, Revelation, Sacrifice)
World Objects: Symbolic items that carry meaning (like Synthia-specific artifacts)
Transformations: Changes in state, location, or knowledge
Step 3: Synthia Grammar
Grammar defines how story components combine.
Node Syntax:
[Thespian] + [Action] + [Target] + [StateChange]
Example: Hero confronts Antagonist → Hero gains insight
Graph Operations:
Merge: Combine two nodes or storylines
Split: Branch story based on Thespian decision
Transform: Apply rule-based transformations to a node (e.g., changing physics or logic)
Overlay: Superimpose latent narrative layers on a visible storyline
Temporal Flexibility:
Linear: Classic timeline
Recursive: Nodes can reference themselves or previous outcomes
Probabilistic: AI generates weighted potential futures
Step 4: AI Integration
AI Functions in Synthia:
Node generation: Create new events from partial human input.
Thespian simulation: Predict Thespian behavior in complex scenarios.
State evolution: Track Thespian growth, mood, knowledge.
Graph optimization: Balance narrative tension, aesthetic beauty, and logic coherence.
Latent space navigation: Explore alternate storylines that humans might not conceive.
Step 5: Symbolic Layer
Each node, Thespian, and object carries a symbolic signature:
Emotional value (joy, fear, curiosity)
Thematic weight (freedom, knowledge, chaos)
Conceptual relevance (innovation, entropy, morality)
Symbols can interact:
Example: Freedom + Knowledge = Enlightenment
Example: Chaos + Obedience = Conflict
This symbolic layer allows AI and humans to speak a shared narrative language.
Step 6: Modular Templates
Hero Journey Module: Flexible, AI-driven template based on archetypes
Conflict Module: Multiple AI-generated conflict scenarios
World Module: AI generates environmental, societal, or fantastical layers
Emotion Module: AI tracks and evolves Thespian emotional trajectories
Step 7: Output and Adaptation
Stories can be output as:
AI-generated films (visual + audio)
Interactive narratives (game-like experiences)
Textual novels (dynamic, evolving)
AI monitors feedback from audience engagement and adjusts future nodes for emergent narrative evolution.
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