Complex Systems EngineeringCSE - SWE 488

Prof. Mohamed Batouche

batouche@ksu.edu.sa

Course information

• Instructors:

– Lectures: Prof. Mohamed Batouche (King Saud University)

– Tutorial: Lecturer (King Saud University) – Mr. Fettouh kellal

– Labs: RA (King Saud University) – Mr. Hanif

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Time schedule (Lectures)

8-9 9-10 10-11 11-12 13-14 14-15 15-16 16-17

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

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Textbook

• Textbook(s): Jay Xiong, New Software Engineering Paradigm

based on Complexity Science, Springer, 2011.

• Recommended books: see website

• Readings: see website

• Lecture slides: some of them are adapted from existing slides …

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Recommended Books• Dan Braha, Ali Minai, Yaneer Bar-Yam (2010): Complex

Engineered Systems: Science Meets Technology. Springer.

• Melanie Mitchell (2009): Complexity: A guided Tour. Oxford University Press.

• Claudios Gros (2011): Complex and Adaptive Dynamical Systems. Second Edition, Springer.

• John H. Miller and Scott E. Page (2007): Complex Adaptive Systems. Princeton  University Press.

• Yaneer Bar-Yam (2004): Making Things Work: Solving Complex problems in a Complex World. NECSI - Knowledge Press.

• Thrishantha Nanayakkara, Mo Jamshidi, Ferat Sahin (2010): Intelligent Control Systems with an Introduction to System of Systems Engineering, CRC Press. 5

Grading policies• Final exam: (40%)

• Midterm1, Midterm 2: (40%)

• Homework, Quizzes, Projects, Attendance: (20%)

• Final grades = Final exam * 0.4 + Midts * 0.4 + HQPA * 0.2

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Course Web

• http://faculty.ksu.edu.sa/mohamedbatouche/Pages/SwE488.aspx/

• Any news for this course.

• Hence, you need to visit it from time to time.

• Suggestions are also welcome!

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Course Description• The course covers at least the followings:

  This course represents an introduction to complex systems and the methods and tools currently under consideration and use towards better understanding of such systems and the development of a complex engineered systems theory. Topics include concepts such as emergence, self-organization, learning and adaptation, and various quantitative and computational intelligence techniques and algorithms that are considered for modeling, analysis and evaluation of such complex systems. System-of-systems concept will be also presented. Students will be able to work on a small project in which they have to design and implement a small part of a complex system. 8

Syllabus: a Tentative• Introduction and definitions• Natural complex systems• Artificial complex systems

– Parts, Wholes and Relationships– Self-organized patterns– Networks and memory– Complexity and Scale in Organizations– Evolution– Competition and cooperation

• The new software engineering paradigm (NSE)• Model driven engineering• Solving complex problems• Concluding remarks, review, and evaluation

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Specific Outcomes of Instruction (Course Learning Outcomes):

• Understand the importance of complexity theory in software development.

• Understand the difference between complex systems and intricate systems.

• Understand complex systems concepts such as emergence, self-organization, adaptation and evolution.

• Learn how to develop evolving large scale software systems.

• Understand the new software engineering paradigm NSE (Nonlinear Software Engineering).

• Use complexity theory to develop complex industrial applications.

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Complex Systems Software Tools

• NetLogo

• Matlab – NN, GA, RBN Toolboxes

• Swarm Platform

• Conway's Game of Life

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