compe 564/ modes 662 natural computing 2013 fall murat karakaya department of computer engineering

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



11. 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?

compe 564/ modes 662 natural computing 2013 fall murat karakaya department of computer engineering

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