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Module 26: Theory, Foundations & Capstone - Why It Works and What You'll Build

The theoretical foundations of EC: runtime analysis, convergence proofs, information geometry, natural gradients, and fitness landscape analysis. Then apply everything in a capstone project: reproduce a paper or solve a real-world problem.

Learning Objectives​

  1. Understand runtime analysis of (1+1)-EA on OneMax and LeadingOnes
  2. Know the convergence proof for (1+1)-ES on Sphere
  3. Understand information geometry and natural gradients (connecting NES to CMA-ES)
  4. Analyze fitness landscapes (ruggedness, neutrality, deceptiveness)
  5. Complete a capstone project demonstrating EC mastery

Concept Explanation​

Coming soon.

Code Examples​

Coming soon.

Exercises​

Coming soon.

Milestone Checklist​

  • Understand basic runtime analysis results
  • Can explain natural gradient connection
  • Completed capstone project
  • Can read and critique EC research papers

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