Moshe Sipper
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Evolutionary Computation
​אלגוריתמים אבולוציוניים

אתר בבנייה
202-2-5651, ​Spring 2021 סמסטר ב
Lecturer: Prof. Moshe Sipper
Administrative Details
  • Prerequisites: Automata, Systems Programming, Algorithms, PPL
  • Credits: 4
  • ​​Grade:
    • 18%: Midterm A
    • 19%: Midterm B
    • 29%: Presentation
    • 34%: Project
  • You must pass all above 4 course components in order to pass the course.
  • Midterm:​
    • If you miss a midterm due to a valid reason according to the university regulations (see Section 7.2), then you will take an oral makeup exam at the lecturer's office, at a date and time decided by the lecturer.
    • If you miss a midterm due to an invalid reason then the midterm's grade will count as 0.
  • Presentation:
    • Each student will present, on their own, a topic/paper from the research literature.
    • The presentation topic/paper must be approved by the lecturer.
    • You must make a selection by April 4, otherwise 10 points will be taken off the final grade.
    • If you do not make a selection by April 11, your presentation grade will be zero.
    • Timeslots will be assigned by the lecturer.
    • Presentation length: 12-15 minutes.
    • Scoring rubric: Organization (6), Knowledge (6), Text (6), Graphics (6), Elocution (4), Eye Contact (1).
  • Project:
    • The project must be done in pairs or threesomes.
    • The topic must be approved by the lecturer.
    • A report must be submitted by the end of the semester (June 18).
    • The report must include the following seven sections:
      1. A short introduction of the domain being investigated.
      2. A description of the problem or phenomenon studied.
      3. An explanation of the methods and algorithms employed.
      4. An overview of the software (not a listing of the code).
      5. An account of the results obtained.
      6. Some interesting conclusions.
      7. Bibliographic references.
    • Language: English or Hebrew.
    • Length: 6-8 pages.
    • Don't include the code in the report.
    • Send the report by e-mail as a PDF file.
Schedule (dates might change!)
  • Mar .. / lecture
Lessons (subject to dynamic changes...)
  • Introduction to Evolutionary Computation
  • What is an Evolutionary Algorithm?
  • Genetic Algorithms
  • GA Theory: Theory, Holland's Schema Theorem, Exact Schema Theorem
  • Local Search Algorithms
  • Working with Evolutionary Algorithms
  • Introduction to Genetic Programming: What is GP? (Koza's vid), GP (Koza), GP (Eiben & Smith), GP Tutorial (Koza), GP Tutorial (Koza & Poli)
  • Evolution of Emergent Cooperative Behavior
  • Koza's vids
  • GP Theory: Poli's Tutorial (see Field Guide, Ch. 11)
  • Game Playing: Adversarial Search
  • Evolving Game-Playing Strategies: Attaining Human-Competitive Game-Playing with GP, GP-Robocode, GP-RARS, GP-Rush & GP-FreeCell
  • Machine learning: Python, evaluation, dataset splits, cross-validation, performance measures, bias/variance tradeoff, visualization, ROC-AUC
  • Supervised learning: models, features, objectives, model training, overfitting, regularization, classification, regression, gradient descent, KNN, linear/logistic regression, decision trees, bagging, ensembling, boosting
  • ​Unsupervised learning: clustering, k-means​
  • ML as part of (the) data science (pipeline)
  • Darwinian Software Engineering
  • Varieties of GP
  • Architecture-Altering Operations
  • Coevolving Sorting Networks
  • Competitive Coevolution
  • Coevolving Solutions to the SCS Problem
  • Parameter Control
  • Evolution Strategies
Literature, vids, datasets, and other resources
Sample midterm questions:
1. TSP: Use order crossover to cross the parents: 
(1 2 3 4 5 6 7 8 9)
(7 8 9 1 2 3 4 5 6) 
2. What does the schema theorem say about the results of a GA run over several generations?
3. What is a coevolutionary algorithm? What are its advantages? Write the pseudocode.
4. What is "ramped half-and-half"?
​5. We wish to solve the N-Queens Problem with a GA. Define a fitness function and a crossover operator for this problem. 
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