Moshe Sipper
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Evolutionary Computation      אלגוריתמים אבולוציוניים

Lecturer: Prof. Moshe Sipper
20225651, Semester Beit, 2015-2016
(Some) Final-Project Reports
  1. Yuval Gelbard & Gal Bar-On, Evolving Agents for "Bomberman"
  2. Idan Hertz, Omer Rimoch, & Lior Guz, Evolutionary AI for Five O' Poker
Administrative Details
  • Prerequisites (for undergraduates): Automata, Systems Programming, Algorithms, PPL
  • Credits: 4
  • Syllabus
  • Time & Place: Wednesday, 10-14, xx/yyy
  • Attendance is obligatory (נוכחות חובה בכל השיעורים). 
    Attendance means: 1. being in class AND 2. arriving on time. 
    One unjustified absence: 0 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.
  • ​Grade:
    • 19%: Midterm
    • 31%: Presentation
    • 50%: 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 you will take an oral makeup exam at the lecturer's office, at a date and time decided by the lecturer.
    • 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 6, otherwise 12 points will be taken off the final grade. If you do not select a topic by April 13, 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 (July 10).
    • 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 or Hebrew.
    • Length: 10-20 pages.
    • Don't include the code in the report.
    • Send the report by e-mail as a PDF file.
Presentations (dates might change!)
May 4:
  1. yuval g, Edge detection in medical images using a genetic algorithm
  2. alex b, Protein Structure Prediction by Applying an Evolutionary Algorithm
  3. gal b, Evolutionary Algorithm Based Offline/Online Path Planner for UAV Navigation
  4. itay a, Towards Human-Competitive Game Playing for Complex Board Games with Genetic Programming
  5. michael m, Evolving Content in the Galactic Arms Race Video Game
  6. niran b, Evolutionary algorithms for de novo drug design
  7. ​slavik n, An evolved circuit, intrinsic in silicon, entwined with physics
May 25:
  1. omri m, Decrypting Substitution Ciphers with Genetic Algorithms
  2. shahaf s, Evolving Effective Micro Behaviors in RTS Game
  3. guy b, A Multiagent Approach to Autonomous Intersection Management
  4. tal a, Malware Detection based on Dependency Graph using Hybrid Genetic Algorithm
  5. lior g, Genetic Programming Produced Competitive Soccer Softbot Teams for RoboCup97
  6. ofir e, A simple genetic algorithm for multiple sequence alignment
  7. gilad h, GP-Rush: Using Genetic Programming to Evolve Solvers for the Rush Hour Puzzle
  8. oren g, Synthesis of Photographic Quality Facial Composites using Evolutionary Algorithms
  9. eldar s, Genetic K-Means Algorithm
Jun 8:
  1. daniel s, Why video games are essential for inventing artificial intelligence
  2. nir s, Evolving Neural Networks Through Augmenting Topologies
  3. omer r, Making Racing Fun Through Player Modeling and Track Evolution
  4. yair b, A genetic algorithm application in bankruptcy prediction modeling
  5. roi v, Evolutionary Music Composition
  6. idan h, An Adaptive Learning Model for Simplified Poker Using Evolutionary Algorithms
  7. yehuda g, Automatic Program Repair with Evolutionary Computation
  8. tal w, Collision Free Path Planning of Cooperative Crane Manipulators Using Genetic Algorithm
  9. or a, Using Genetic Algorithm for network intrusion detection
Schedule (not final)
Mar 9 / lecture
Mar 16 / lecture
Mar 23 / purim
Mar 30 / lecture
Apr 6 / lecture
Apr 13 / lecture
Apr 20 / pessach
Apr 27 / pessach
May 4 / midterm + presentations
May 11 / yom hazikaron
May 18/ guest talk
May 25/ presentations
Jun 1 / yom hastudent
Jun 8 / presentations
Jun 15 / project
Jun 22 / project
Jun 29 / 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: Attaining Human-Competitive Game-Playing with GP, GP-Robocode, GP-RARS, GP-Rush & GP-FreeCell
  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

Shortish (possibly fun) reads :
  • 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
  • Why video games are essential for inventing artificial intelligence
  • Biologic or “By Ole Logic”
Reference texts:
  • 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.
  • 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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