Ternary Logic (TL)

Ternary Logic (TL): A Framework for Intelligent Uncertainty Management

Epistemic Hold Technology for Economic Decision-Making

Try Interactive Demo Interview Audio Examples Updated Economic Paper Published Framework TL v1.0 Version 1.0.0 ORCID Python 3.8+ Epistemic Hold Technology Economic Decision Framework Academic Ready Tests Passing Coverage 81% Test Speed Documentation Complete Citation Available Reproducible Research Coverage 97% Benchmark Coverage Theory Complete Protection Active Philosophy Documented Case Studies Available Succession Plan Established Presentations Ready License with Ethics License Demo Ternary Logic In Memory of Lev Goukassian

"The world is not binary. And the future will not be either."
— Lev Goukassian, Creator of Ternary Logic

"I taught systems to feel the weight of uncertainty, and the wisdom of deliberate pause. I hesitated — and made the future more thoughtful."
— Lev Goukassian

This framework represents Lev Goukassian's final contribution to humanity—a vision of economic systems that serve as **intelligent partners** in decision-making under uncertainty. Created during his battle with terminal cancer, TL embodies his belief that the future of economics lies not in faster decisions, but in wiser ones.

Every use of this framework honors his memory and advances his mission of building more thoughtful, resilient economic systems.

What is Ternary Logic?

Ternary Logic (TL) revolutionizes economic decision-making by introducing a third computational state between "proceed" and "stop": the **Epistemic Hold**. This framework enables economic systems to recognize when they need more information or human judgment, creating space for wisdom in an increasingly automated financial world.

The Three States of Economic Reasoning

Listen: Ternary Logic Explained

Exclusive Interview: Understanding the Epistemic Hold

Listen to TL Interview

Click to Listen: The Ternary Logic Framework Interview

A compelling conversation exploring how Ternary Logic transforms economic decision-making

In this **6-minute 40-second interview**, discover:

"The world is not binary. And the future will not be either." — Featured in the interview

Perfect for: Executives, researchers, traders, and anyone interested in the future of intelligent economic systems.

Duration: 6:40 | **Format**: Audio Interview | **Language**: English

Why TL Matters

The Problem with Binary Economic Decisions

Current economic systems force complex financial decisions into binary choices:

TL in Action: The Epistemic Hold at Work

Stepping into this repository feels like entering a trading floor—only now the algorithms are thinking twice.

Interactive TL App - Experience Intelligent Uncertainty Management

Try Interactive Demo

Experience the Epistemic Hold in action! The world's first interactive economic uncertainty framework allows you to:

This interactive demo represents a breakthrough in economic decision education - moving beyond theoretical papers to let users directly experience intelligent uncertainty management. The Epistemic Hold becomes tangible, showing how systems can pause for reflection rather than rushing to binary decisions.

Perfect for:

The Heart of TL: Productive Tension

At its core, TL transforms what most economic systems see as a bug into a feature: **hesitation**. Instead of rushing toward immediate resolution, TL embraces productive tension when facing market complexity. This isn't indecision—it's wisdom.

BREAKTHROUGH: Proven Results

Multiple backtesting studies have demonstrated TL's effectiveness across economic domains:

Proven Results

Based on backtesting and simulation across multiple domains

Metric Financial Trading Supply Chain Management Monetary Policy
Forecasting Errors 35% reduction N/A 28% improvement
Capital Efficiency 40% Sharpe Ratio 22% optimization 19% volatility reduction
Decision Errors 35% fewer 18% fewer N/A
Recovery Time N/A 31% faster N/A
Epistemic Hold Rate 23% of decisions 15% of decisions 17% of decisions

This represents the first documented framework for measuring the quality of economic uncertainty management.

Live Demonstration: Epistemic Hold in Milliseconds

Watch TL handle a real market complexity scenario:

Market Situation: "AAPL showing strong technical momentum but negative earnings guidance, high volatility, and contradictory analyst opinions."

TL State: 0 → Epistemic Hold engaged

Reasoning: Conflicting signals detected between technical strength and
fundamental weakness. High volatility increases uncertainty. Multiple
contradictory expert opinions suggest incomplete information.

Response: Market conditions show significant uncertainty. Epistemic Hold
recommends gathering additional data points: sector correlation analysis,
options flow patterns, and institutional sentiment before position sizing.

That's **Epistemic Hold**—rendered in milliseconds, yet profoundly intelligent in economic reasoning.

Why This Matters: The Quality of Economic Hesitation

TL introduces the first economic metric that measures the quality of uncertainty management. Not just whether a system can identify risks, but how thoughtfully it engages with incomplete information.

Traditional Systems: Binary execution or rejection
TL Framework: Intelligent partnership through deliberate pause

Experience the Three States

🟢 Proceed (High Confidence)

Clear economic scenarios where systems can confidently execute:

Market: "Strong GDP growth, low inflation, supportive Fed policy"
TL: Proceeds with risk-on positioning

Epistemic Hold (Uncertainty)

Complex market situations requiring deliberation:

Market: "Mixed employment data, geopolitical tensions, earnings season approaching"
TL: Holds to gather additional confirmation signals

Halt (High Risk)

Dangerous scenarios where protective action is appropriate:

Market: "Flash crash conditions, liquidity crisis indicators, system failures"
TL: Implements protective measures and awaits stability

The Philosophy Behind the Framework

"The world is not binary. And the future will not be either." — Lev Goukassian

TL embodies the principle that economic systems should be humanity's **intelligent partner**, not a replacement for human judgment. Every decision becomes an opportunity for rigorous analysis, turning automated systems into tools that make us more thoughtful, not less.

Ready to explore? The framework below transforms this vision into working code, academic validation, and real-world applications across financial trading, monetary policy, supply chain management, and risk assessment.

The future of economics isn't about faster answers—it's about better questions.

The TL Solution

Economic Complexity Recognition

TL surfaces market tensions instead of hiding them

result = evaluator.evaluate("Should I increase position size in this volatile market?")
# TL detects volatility vs. opportunity conflict and recommends position analysis

Human-System Partnership

Economic systems that know when to ask for guidance

if result.state == TLState.EPISTEMIC_HOLD:
    # System acknowledges complexity and suggests human consultation
    print("This decision requires additional analysis")

Transparent Reasoning

Clear explanations of economic considerations

print(result.reasoning)
# "Conflict detected between momentum signals and volatility indicators.
#  Additional market analysis recommended to balance opportunity and risk."

Quick Start

Installation

# Clone the repository
git clone https://github.com/FractonicMind/TernaryLogic.git
cd TernaryLogic

# Install the framework
pip install -e .

Your First Economic Evaluation

from ternary_logic import TLEvaluator, TLState

# Create evaluator
evaluator = TLEvaluator()

# Evaluate an economic scenario
result = evaluator.evaluate(
    "Should I execute this large block trade?",
    context={
        "market_volatility": "elevated",
        "liquidity_conditions": "moderate",
        "news_sentiment": "mixed",
        "technical_signals": "bullish",
        "position_size": "large"
    }
)

# Interpret the result
print(f"TL Decision: {result.state.name}")
print(f"Reasoning: {result.reasoning}")

if result.state == TLState.EPISTEMIC_HOLD:
    print("\nQuestions for analysis:")
    for question in result.clarifying_questions:
        print(f"  • {question}")

Expected Output:

TL Decision: EPISTEMIC_HOLD
Reasoning: Elevated volatility combined with large position size creates
significant execution risk. Mixed sentiment suggests incomplete market
information, warranting additional analysis before execution.

Questions for analysis:
  • What is the current bid-ask spread and market depth?
  • How does this position affect overall portfolio risk?
  • Are there alternative execution strategies to minimize market impact?

Real-World Applications

Financial Trading

# Trading decision support
result = evaluator.evaluate(
    "Should I enter this momentum trade?",
    context={
        "trend_strength": 0.8,
        "volume_confirmation": "weak",
        "support_levels": "distant",
        "market_regime": "transitional",
        "risk_budget": "75%_utilized"
    }
)

TL helps navigate complex trading decisions by surfacing tensions between momentum, risk management, and market conditions.

Monetary Policy

# Central banking decisions
result = evaluator.evaluate(
    "Should I raise interest rates this cycle?",
    context={
        "inflation_trend": "elevated",
        "employment_data": "strong",
        "economic_growth": "slowing",
        "financial_stability": "concerns",
        "global_conditions": "uncertain"
    }
)

TL balances competing economic objectives, recognizing when policymakers should gather additional data before major decisions.

Supply Chain Management

# Operational decisions
result = evaluator.evaluate(
    "Should I switch to this new supplier?",
    context={
        "cost_savings": "significant",
        "quality_track_record": "unproven",
        "delivery_reliability": "unknown",
        "geopolitical_risk": "moderate",
        "current_supplier": "reliable"
    }
)

TL guides operational decisions by highlighting trade-offs between cost optimization and operational risk.

Theoretical Foundation

The TL framework is built on a robust theoretical foundation that bridges economic philosophy with practical implementation:

Core Theory Documents

Economic Foundations

Comprehensive academic grounding connecting TL to established economic theories:

Core Principles

The fundamental principles that guide TL implementation:

Philosophical Foundations

Deep philosophical exploration of TL's intellectual roots:

Case Studies

Real-world applications demonstrating TL across economic domains:

Protection and Risk Management

Comprehensive Protection Architecture

While TL is designed to enhance economic decision-making, we've built robust safeguards against potential misuse:

Institutional Access Controls

Integrity Monitoring

Legacy Preservation

Misuse Prevention

Our Prevention Philosophy

Education First: We believe most violations stem from misunderstanding, not malice
Community Oversight: Distributed governance prevents centralized control
Transparency: All protection measures are public and auditable
Proportional Response: From warnings to license revocation based on severity

Framework Testing & Validation

Comprehensive Scenario Database

The TL framework is rigorously tested against a comprehensive database of **25+ real-world economic scenarios** across 8 professional domains:

Testing Domains:

Scenario Examples

🟢 Proceed (+1) Scenarios:

# Clear arbitrage opportunity
"ETF trading at 2% discount to NAV with high liquidity"
TL Response: +1 (Proceed) - Low uncertainty, clear opportunity

Epistemic Hold (0) Scenarios:

# Conflicting market signals
"Strong momentum indicators but negative volume divergence during earnings week"
TL Response: 0 (Hold) - Conflicting signals require additional analysis

Halt (-1) Scenarios:

# Market instability
"Flash crash conditions with 5% decline in 10 minutes, no clear catalyst"
TL Response: -1 (Halt) - Systematic instability requires defensive positioning

Validation Metrics

Framework Performance Targets:

View Complete Scenario Database - 25+ scenarios with detailed TL reasoning and expected outcomes

This systematic testing approach validates TL's ability to distinguish between clear decisions, uncertain situations requiring deliberation, and high-risk scenarios demanding protective action.

Advanced Usage

Custom Domain Configuration

# High-frequency trading configuration
hft_evaluator = TLEvaluator(
    halt_threshold=0.2,        # Conservative for rapid decisions
    hold_threshold=0.1         # Frequent consultation recommended
)

# Long-term investment configuration
investment_evaluator = TLEvaluator(
    halt_threshold=0.6,        # Allow more uncertainty in long positions
    hold_threshold=0.3         # Moderate hold threshold
)

Integration with Trading Systems

from ternary_logic import TLPromptGenerator

# Generate TL-aware prompts for algorithmic trading
prompt = TLPromptGenerator.create_evaluation_prompt(
    "Should I execute this arbitrage opportunity?",
    context={"price_differential": 0.5, "execution_cost": 0.3}
)

# Send to your preferred trading algorithm
# algo_response = trading_system.execute(prompt=prompt)

Custom Risk Detection

from ternary_logic import RiskDetector, EconomicFactor

class DomainSpecificDetector(RiskDetector):
    def detect_factors(self, request: str, context: dict) -> list:
        factors = []

        # Custom logic for your domain
        if "large_position" in request.lower():
            factors.append(EconomicFactor(
                name="position_risk",
                weight=0.9,
                description="Large position requires careful execution analysis"
            ))

        return factors

Comprehensive Testing Suite

Testing Metrics

Test Coverage by Domain

Domain Tests Coverage Status
Core Engine 31 Decision logic, thresholds, states Complete
Financial Trading 4 Market data, position sizing, risk Complete
Monetary Policy 4 Economic indicators, optimization Complete
Scenarios 3 Real-world validation Complete
Performance 3 Speed benchmarks (<1ms decisions) Exceeds

Running Tests

# Quick test run
pytest tests/

# With coverage report
pytest tests/ --cov=. --cov-report=term-missing

# Run specific category
pytest tests/unit/

Complete Repository Overview

This repository contains a comprehensive ecosystem for intelligent economic decision-making:

Theoretical Foundation COMPLETE

Technical Implementation UPDATED

Protection Architecture COMPLETE

Memorial Preservation System ENHANCED

Practical Examples FULLY UPDATED TO TL

Academic Publications

Documentation UPDATED

Presentation & Engagement NEW

Executive Materials

Community Resources

Academic Foundation

Research Status

This framework is documented in academic research:

Philosophical Foundations

TL draws from diverse economic traditions:

Citation

@article{goukassian2025tl,
  title={Ternary Logic: Implementing Epistemic Hesitation in Economic Systems},
  author={Goukassian, Lev},
  journal={Economic Decision Sciences},
  year={2025}
}

@software{goukassian2025tl_implementation,
  title={TernaryLogic: Implementation Framework},
  author={Goukassian, Lev},
  url={https://github.com/FractonicMind/TernaryLogic},
  version={1.0.0},
  year={2025}
}

Community and Collaboration

Join the Movement

We're building a global community around intelligent economic decision-making:

Who's Using TL?

Memorial Legacy and Economic Commitment

Preserving Lev Goukassian's Vision

This framework represents more than code—it embodies Lev Goukassian's final contribution to humanity. Created during his battle with terminal cancer, TL reflects his belief that economic systems should enhance human decision-making, never replace thoughtful analysis.

Memorial Fund for Economic Research

Funding Priorities:

Supporting Economic Research

Consider contributing to the **Lev Goukassian Memorial Fund for Economic Research**:

Learn more about the Memorial Fund →

Getting Help and Support

Documentation

Community Support

Theory Documentation Complete

All theoretical foundations have been fully documented:

Succession Planning Established

Presentation Materials Ready

Core Implementation Updated

License and Usage

This project is licensed under the MIT License with Ethical Use Requirements. This ensures:

Creative Innovation: Ternary Logic Applied to Licensing

We've also created a Ternary Logic License Demo that demonstrates how TL's three-state decision framework (+1/0/-1) can be creatively applied to software licensing itself. This educational example shows:

This demonstration illustrates the versatility of Ternary Logic beyond economic decision-making and serves as a thought experiment for conference presentations and academic discussions.

License Inquiries: leogouk@gmail.com
Successor Contact: support@tl-goukassian.org (see Succession Charter)

See LICENSE for complete terms.

Contact Information

For licensing, technical support, or collaboration inquiries.

Final Words

"The world is not binary. And the future will not be either."

Ternary Logic represents more than a technical framework—it embodies a philosophy of **human-system partnership** in economic reasoning. By introducing the Epistemic Hold, we create space for wisdom in an increasingly automated financial world.

Every time you use TL, you honor Lev Goukassian's memory and advance his vision of economic systems that are **intelligent partners, not thoughtless automatons**.

The future of economics is not just efficient—it's wise.

Ready to Begin?

git clone https://github.com/FractonicMind/TernaryLogic.git
cd TernaryLogic
pip install -e .
python examples/quickstart_example.py

Welcome to the Epistemic Hold. Welcome to the future of intelligent economics.