🧠 Symbolos Core

Symbolos Core is a meta-systems substrate, a symbolic simulation and transformation engine. It enables programmable worlds, causal pipelines, and agent-based symbolic reasoning using structured Functors and Pipelines.

This core module provides the universal symbolic substrate for higher-level applications in narrative AI, procedural metaphysics, planning, and beyond.

Based in Category Theory, the Symbolos Core packs a lot into under 500 line of code.

❓ Why Symbolos Core?

Symbolos Core is designed for researchers, system architects, and AI builders who want a programmable foundation for simulating and transforming symbolic systems. It enables composable, introspectable worlds with structured change over time.

Common use cases include:

• Simulation of agents and symbolic environments
• Symbolic planning, memory, and world forking
• Procedural metaphysics and world generation
• Building blocks for language, art, and cognition tools

🧠 Core Concepts

• World — a symbolic state container with composable tick-based change
• Object — the atomic symbolic unit (e.g. Note, Agent, Cell) with type, status, and tick
• Functor — a transformation unit that mutates a world in context
• Pipeline — a sequence of functor steps run over time
• Agent — a symbolic entity that can perceive and alter the world

🚀 Getting Started

To create and run a symbolic pipeline:

import { World, runPipeline } from "@radcliffetech/symbolos-core";

const world = World.createWorld();
const steps = [...]; // define your FunctorSteps

const result = await runPipeline({ world, steps });

🧩 License

The Symbolos Core engine is licensed under the MIT License.

This license applies to the symbolic execution substrate, including:

• Core types
• Functors
• Pipeline execution

🔐 Dual Licensing Notice

Domain-specific extensions of Symbolos — including pipelines, cognitive agents, metaphysical simulation layers, and advanced orchestration — are not included in this license.

These components are protected intellectual property and may be:

• Licensed separately for research or commercial use
• Reserved for internal or future public distribution

For access or licensing inquiries, contact Jeffrey Radcliffe at [email protected].