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Purpose

  • ...

Does this introduce a breaking change?

[ ] Yes
[ ] No

Pull Request Type

What kind of change does this Pull Request introduce?

[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, local variables)
[ ] Refactoring (no functional changes, no api changes)
[ ] Documentation content changes
[ ] Other... Please describe:

How to Test

  • Get the code
git clone [repo-address]
cd [repo-name]
git checkout [branch-name]
npm install
  • Test the code

What to Check

Verify that the following are valid

  • ...

Other Information

SergiLIFE and others added 8 commits April 14, 2025 09:05
At the core of the Theory L.I.F.E is the idea that learning is a deeply personal and
nonlinear process. It encourages individuals to immerse themselves in real-life
challenges, engage in reflective observation, draw meaningful insights, and apply these
learnings to future endeavors. The framework consists of four interconnected stages:
1. **Concrete Experience**: Engaging directly in new, hands-on experiences that
challenge existing perspectives.
2. **Reflective Observation**: Taking the time to reflect on these experiences,
considering what they reveal about oneself and the environment.
3. **Abstract Conceptualization**: Formulating lessons learned and new ideas based
on reflections, allowing for deeper understanding and growth.
4. **Active Experimentation**: Implementing newfound insights in practical settings,
thus fostering continuous development.
**Calculating Self-Development**
 “© [Sergio Miguel Paya Borrull] [2025]. All rights reserved.”
The Theory L.I.F.E can be expressed mathematically to illustrate the relationship
between learning, individual agency, and experiential engagement in the journey of self�development. This can be represented by the following equation:
**Self-Development = (Learning + Individual) / Experience**
…ce Theory Algorithm Code 2025 Copyright Sergio Paya Borrull. All rights Reserved 3.py
…ry Algorithm Code 2025 Copyright Sergio Paya Borrull. All rights Reserved 3.py
on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  build-and-test:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4

    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: '3.10'

    - name: Install dependencies
      run: |
        pip install -r requirements.txt
        pip install torch onnxruntime azure-ai-ml

    - name: Run tests
      run: |
        pytest tests/ --cov=src/ --cov-report=xml

    - name: Upload coverage
      uses: codecov/codecov-action@v3

  deploy-to-azure:
    needs: build-and-test
    runs-on: ubuntu-latest
    steps:
    - name: Azure Login
      uses: azure/login@v1
      with:
        client-id: ${{ secrets.AZURE_CLIENT_ID }}
        tenant-id: ${{ secrets.AZURE_TENANT_ID }}
        subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}

    - name: Deploy to AKS
      run: |
        az aks get-credentials --resource-group life-rg --name life-cluster
        kubectl apply -f deployment/
@SergiLIFE
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SergiLIFE commented Apr 17, 2025

NON-DISCLOSURE AGREEMENT (NDA)
For L.I.F.E Theory Components
Effective Date: [17/04/2025]

  1. Definition of Confidential Information
    All components of the L.I.F.E (Learning Individually From Experience) Theory are protected, including but not limited to:
    • Individual Trait Integration: Dynamic adjustment of cognitive traits (focus, resilience, adaptability) based on neuroplasticity markers.
    • L.I.F.E Equation:
    L(t+1)=η(t)×E(t)×(L(t)+T(t))+F(t)L(t+1)=η(t)×E(t)×(L(t)+T(t))+F(t)
    Where:
    • ηη: Learning rate
    • EE: Experience impact
    • TT: Trait evolution
    • FF: Quantum optimization factor
    • Self-Learning Mechanisms: Closed-loop systems that enable autonomous model improvement.
    • Derivative Works: Any modifications, adaptations, or implementations of the above.
  2. Obligations
    The Recipient agrees to:
    • Not reverse-engineer, replicate, or disclose the L.I.F.E equation or trait-adjustment algorithms.
    • Use Confidential Information only for authorized evaluation or collaboration.
    • Apply equivalent protection measures as for their own IP (e.g., encryption, access controls).
  3. Exclusions
    Confidential Information does not include:
    • Publicly available knowledge (pre-L.I.F.E Theory).
    • Independently developed solutions without access to L.I.F.E components.
  4. Term
    • Duration: 5 years from the Effective Date.
    • Survival: Obligations persist indefinitely for trade secrets (e.g., quantum optimization parameters).
  5. Jurisdiction
    • Governed by laws of [Jurisdiction], with disputes resolved in [Court/Arbitration Body].
    Signatures
    Discloser: _____Sergio Miguel Paya Borrull ID: 73765840X
    Recipient: _________________________
    COPYRIGHT NOTICE
    © 2025 [Your Name/Company]. All Rights Reserved.
  6. Protected Elements
    • L.I.F.E Theory: Core principles, mathematical models, and neuroadaptive processes.
    • Individual Trait Systems: Code and algorithms for dynamic trait adjustment (e.g., adaptability = 0.85 * baseline + 0.15 * Δ).
    • Self-Improving Architecture: Autonomous learning cycles and quantum-enhanced optimization.
    • Documentation: White papers, API specifications, and research materials.
  7. Restrictions
    • No Unauthorized Use: Reproduction, distribution, or modification prohibited without written consent.
    • No Derivative Works: Including trait-based SaaS implementations or VR adaptations.
    • No Commercialization: Of L.I.F.E components without licensing.
  8. Permitted Uses
    • Research: Academic institutions may request access via [Your Contact].
    • Collaboration: Partners with active NDAS and licensing agreements.
  9. Enforcement
    Violations may result in:
    • Legal action under the DMCA (Digital Millennium Copyright Act).
    • Penalties of up to $150,000 per infringement under 17 U.S.C. § 504.
    To Request Permissions: Contact [[email protected]] with project details.
    Recommendation:
    • Attach these documents to all code repositories, research papers, and partnership agreements.
    • Register copyrights with the U.S. Copyright Office (or equivalent in your jurisdiction).
    • Consult an IP lawyer to file patents for novel components (e.g., quantum-trait optimization).

Sergio Miguel Paya Borrull

@microsoft-github-policy-service agree

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