Moshe Sipper
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Evolutionary Computation      אלגוריתמים אבולוציוניים

Lecturer: Prof. Moshe Sipper
20225651, Semester Beit, 2014-2015
This course will be given in English.  Lectures, presentations, midterm, projects, reports will be in English.
Announcements
  • Minor changes to May 6 and May 20 presentation schedules.
  • Reminder: May 6 -- midterm and presentations, May 20 -- presentations. Presentations should take between 12-15 minutes -- no less, no more. Midterm and presentations -- in English.
  • The GECCO 2014 proceedings are available via http://dl.acm.org/citation.cfm?id=2576768 (to access articles freely you need to be on the university network, either physically or via proxy)
Projects
  1. Ken S and Dafna V, A Genetic Algorithm for Ciphertext-Only Attack in Cryptanalysis
  2. Marina S, Kosta S, Zohar K, Genetic algorithm for efficient equilibria in the "best-shot" public goods game
  3. Yoaz M, Irina K, Evolving winning decks for Hearthstone
  4. Kiril Y, Evolutionary top-down induction of decision trees
  5. Pavel R, Adam D, Ziv A, Hybrid Evolutionary Algorithms for Graph Coloring
  6. Eyal B, Eli S, Michael A, Evolving pictures of human faces using GA
Presentations
 May 6:
  1. Chen E, Evolutionary Design of FreeCell Solvers
  2. Dafna V, Encouraging Creative Thinking in Robots Improves Their Ability to Solve Challenging Problems
  3. Pavel R, A novel human-computer collaboration: combining novelty search with interactive evolution
  4. Irina K, Evolution of honest signaling by social punishment
 May 20:
  1. Zohar K, An Evolutionary Multi-Agent System for Database Query Optimization
  2. Ella I, Multiobjective Pressurized Water Reactor Reload Core Design by Nondominated Genetic Algorithm Search
  3. Marina S, Generalized Asymmetric Partition Crossover (GAPX) for the Asymmetric TSP
  4. Ziv A, Hybrid Evolutionary Algorithms for Graph Coloring
  5. Adam D, Efficient solutions for Mastermind using genetic algorithms
  6. Kiril Y, A Tribal Ecosystem Inspired Algorithm (TEA) For Global Optimization
  7. Ken S, A Genetic Algorithm for Ciphertext-Only Attack in Cryptanalysis
  8. Konstantin S, Novelty search creates robots with general skills for exploration
  9. Eyal B, Genetic algorithm-based solver for very large multiple jigsaw puzzles of unknown dimensions and piece orientation
  10. Yoaz M, Evolving Successful Stack Overflow Attacks for Vulnerability Testing
  11. Michael A, Generating Mimicry Attacks using Genetic Programming: A Benchmarking Study
  12. Eli S, Passive Solar Building Design Using Genetic Programming
Administrative Details
  • Prerequisites (for undergraduates): Automata, Systems Programming, Algorithms, PPL
  • Credits: 4
  • Syllabus
  • Time & Place: Wednesday, 10-14, 32/114
  • Attendance is obligatory (נוכחות חובה בכל השיעורים). 
    Attendance means: 1. being in class, and 2. arriving on time. 
    One unjustified absence: 2 points off final grade. Two unjustified absences: 5 points off final grade. Three or more unjustified absences: final grade is ZERO. Justified absence is one of those appearing in Section 7.2 here; any other absence is UNJUSTIFIED.
  • 1-point bonus for attending all classes during tkufat shinuyim. 
  • Grade:
    • 29%: Midterm
    • 31%: Presentation
    • 40%: Project
  • Midterm:
    • You must pass the midterm in order to pass the course.
    • If you miss the midterm due to a valid reason according to the university regulations (see Section 7.2), then your grade will be calculated according to: Project (50%) and Presentation (50%).
    • If you miss the midterm due to an invalid reason then the midterm's grade will count as 0.
    • Sample midterm questions.
  • Presentation:
    • Each student will present on his own a paper(s) from the research literature.
    • The presentation topic must be approved by the lecturer.
    • You must select a topic by April 8, otherwise 12 points will be taken off the final grade. If you do not select a topic by April 15, 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 (5), Elocution (5), Eye Contact (3).
  • Project:
    • The project must be done in pairs or threesomes.
    • The project topic must be approved by the lecturer.
    • The project report must be submitted by the end of the semester (June 26).
    • The project 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.
    • Length: 10-20 pages.
    • Don't include the code in the report.
    • Don't send the report by e-mail: hand in a hard copy.
Schedule (not final)
Mar 11 / lecture
Mar 18 / lecture
Mar 25 / lecture
Apr 1 / pesach
Apr 8 / pesach
Apr 15 / lecture
Apr 22 / yom hazikaron
Apr 29 / lecture
May 6 / midterm + presentations
May 13 / 10: Dr. Achiya Elyasaf
              12: Dr. Amit Benbassat
May 20 / presentations
May 27 / yom hastudent
Jun 3 / project
Jun 10 / project
Jun 17 / project
Jun 24 / project
Lessons
  1. Introduction to Evolutionary Computation
  2. What is an Evolutionary Algorithm?
  3. Genetic Algorithms
  4. GA Theory: Theory, Holland's Schema Theorem, Exact Schema Theorem
  5. Local Search Algorithms
  6. Working with Evolutionary Algorithms
  7. Introduction to Genetic Programming: What is GP? (Koza's vid), GP (Koza), GP (Eiben & Smith), GP Tutorial (Koza), GP Tutorial (Koza & Poli)
  8. Evolution of Emergent Cooperative Behavior
  9. Koza's vids
  10. GP Theory: Poli's Tutorial (see Field Guide, Ch. 11)
  11. Game Playing: Adversarial Search
  12. Evolving Game-Playing Strategies: GP-Robocode, GP-RARS, GP-Rush & GP-FreeCell, Attaining Human-Competitive Game-Playing with GP
  13. Darwinian Software Engineering
  14. (Varieties of GP)
  15. (Architecture-Altering Operations)
  16. (Coevolving Sorting Networks)
  17. (Competitive Coevolution)
  18. (Coevolving Solutions to the SCS Problem)
  19. (Parameter Control)
  20. (Evolution Strategies)
Literature

Introductory:
  • Evolutionary Algorithms
  • Genetic and Evolutionary Algorithms and Programming
  • הרצאת מבוא של גיא כתבי , בוגר הקורס "אלגוריתמים אבולוציוניים וחיים מלאכותיים", 2006
  • Some reports in the popular press
Primary:
  • M. Sipper, Evolved to Win, Lulu, 2011. (freely downloadable)
  • M. Sipper, Machine Nature: The Coming Age of Bio-Inspired Computing, McGraw-Hill, New York, 2002.
  • A.E. Eiben and J.E. Smith, Introduction to Evolutionary Computing, Springer, 1st edition, 2003, Corr. 2nd printing, 2007.
  • R. Poli, B. Langdon, & N. McPhee, A Field Guide to Genetic Programming, 2008. (freely downloadable)
  • J. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA, 1992.
Also:
  • S. Luke, Essentials of Metaheuristics, 2010. (freely downloadable)
  • Z. Michalewicz & D.B. Fogel, How to Solve It: Modern Heuristics, 2nd ed. Revised and Extended, 2004.
  • Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, Berlin, 3rd edition, 1996.
  • D. Floreano & C. Mattiussi, Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, MIT Press, 2008.
  • A. Tettamanzi & M. Tomassini, Soft Computing: Integrating Evolutionary, Neural, and Fuzzy Systems, Springer-Verlag, Heidelberg, 2001.
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