DSFT-TD V2.1 Documentation

📖 Overview

"Meaning is not a point in space. It is the dynamics of interaction between opposing forces."

"The observer is not neutral — it actively modifies the field it measures."

DSFT-TD V2.1 (Dynamic Semantic Field Theory - Temporal Dynamics) is a temporal framework for modeling semantic dynamics as interacting forces rather than static classifications. Unlike traditional NLP classifiers that assign single labels to text, DSFT treats dialogue as a field of four interacting semantic forces.

The semantic forces introduced in DSFT are operational modeling constructs rather than claims about biological cognition, quantum mechanics, or consciousness.

🧠 The Four Semantic Forces (Operational Constructs)

📐 Core Equations

Parameters

🔭 Observer Modes

Four configurable observer modes alter how the semantic field is sampled. This is a configurable architectural choice, not a claim about quantum measurement.

📦 Installation

# Clone the repository
git clone https://github.com/gitdeeper12/IKPS-CORE.git
cd IKPS-CORE

# Install dependencies
npm install

# Run all benchmarks
npm run benchmark:all

# Run individual benchmarks
npm run benchmark:transitions
npm run benchmark:latency
npm run benchmark:drift
npm run benchmark:stability

Python Package

pip install ikps-core

🔧 API Reference

DSFTTDV2 — Core Engine

const { DSFTTDV2 } = require('./src/transition/dsft_td_v2.js');

const engine = new DSFTTDV2({
    inertia: 0.2,
    coupling: 0.25,
    momentum: 0.5,
    hysteresis: 0.1,
    observerMode: 'passive'
});

// Process dialogue turn
const forces = engine.update(dialogueTurn);
const precursor = engine.getPrecursorProbability();
const dominant = engine.getDominantForce();

DSFTTDV2 Parameters

🧩 Core Modules

📊 Validation Summary

Transition Detection

Stability Metrics

👤 Author

📝 Citation