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COMPE 564/ MODES 662 Natural Computing
2013 Fall
Murat KARAKAYA Department of Computer Engineering
COMPE 564 / MODES 662 Natural Computing
• Instructors : Murat KARAKAYA• Email : [email protected]• Office : Z-14 • Lecture : Wednesday 14:30-17:20 @ 2031• Office Hour : Wednesday 14:00-14:30
• Teaching Asst.: TBD• Email : TBD• Office : TBD • Course Web page is on Moodle: Check your registration!
Objectives & Content
Objectives:
• to teach different nature inspired computing techniques;
• to gain an insight about how to solve real-life practical computing and optimization problems.
Objectives & Content
• Gain necessary knowledge about nature-inspired computing mechanisms, including Hill Climbing, Simulated Annealing, Genetic Algorithms, Neural Networks, Swarm Intelligence (e.g. Ant Colonies, Particle Swarm Optimization) and Artificial Immune Systems.
• Understand and improve the mentioned nature inspired computing techniques
• Applying the nature-inspired computing techniques to real-life practical problems
• Develop necessary software codes in the nature-inspired computing context.
Text Books and ReferencesCourse Book: 1. Leandro Nunes de Castro, Fundamentals of Natural Computing:
Basic Concepts, Algorithms and Applications, Chapman & Hall/CRC, 2006, ISBN 1-58488-643-9.
Other Sources:1. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach,
Prentice-Hall, 2003, ISBN: 0-13-790395-22. J. Hertz, A. Krogh and R.G. Palmer, Introduction to the Theory of
Neural Computation, Addison-Wesley Publishing Company, 1991, ISBN: 0-201-50395-6.
3. M. Dorigo and T. Stützle, Ant Colony Optimization, MIT Press, 2004. ISBN: 0-262-04219-3
4. Artificial Intelligence, Patrick H. Winston, Addison-Wesley, 1992. ISBN: 0-201-533774
Grading (Tentative)
• Presentations ?%• Reports ?%• Demo ?%• Midterms ?%• Final Exam ?%
– Passing grade DD >= 60 FD<=59!
– No bell curve! Catalog will apply
Grading Policies• Missed exams:
o no make-up exam for midterms without approved excuse!o no make-up exam for final for any excuse!
• Ethics:o All assignments/projects are to be your own work.
• Participation:o You are supposed to be active in the class by involving and
participating disscusions via asking questions, proposing solutions, explaning your ideas, etc.
WEEKLY SCHEDULE AND PRE-STUDY PAGES
1. Week Introduction to Natural Computing Ch.1
2. Week Introduction to Natural Computing (Self Study)Problem Solving by Search (Hill Climbing; Simulated Annealing)
Ch.2
3. Week Presentations: Genetic AlgorithmsArtificial Neural Networks
Chapter3 & Source #1
4. Week Presentations: Artificial Neural Networks Artificial Bee Colony Optimization
Chapter & Source #2
5. Week Presentations: Ant Colony OptimizationParticle Swarm Optimization
Chapter 5 (Course Book) and Source #3
6. Week Optimization Problem Appendix B
7. Week Natural Computing Solution Designs for Selected Optimization Problems
8. Week Implementation of Natural Computing Solution
9. Week Implementation of Natural Computing Solution
10. Week Implementation of Natural Computing Solution
11. Week Demo and Presentations of the solution
12. Week Demo and Presentations of the solution
13. Week Demo and Presentations of the solution
14. Week Final Report Sunmissions and Presentation
15. Week Final Exam
16. Week Final Exam
Literature Survey Presentation Schedule
• GA– Halil Savuran W3
• NeuralComp– Kerem Yücel W3
– Kaled Alhaddat W4
• ABC– Arda Sezen W4
• ACO– Emre Tuner W5
• Particle Swarm– Hamdi Demirel W5
WORK LOAD & EXPECTED SKILLS
Need to have a copy of the Text Book
You have to read the chapters in the book and research for the related papers.
You have to take note during the lectures or classes.
You will present, teach & report your topic/worki
You will code your solution to the selected problem.
Finally; you are expected to write a paper & submit to a conference
You are supposed to be good at–Coding - Algorithms–Linear Programming - Data Structures–Report writing & presenting - Self-motivated
Any Questions?