1. Complex Systems Engineering CSE - SWE 488 Prof. Mohamed Batouche batouche@ksu.edu.sa

2. 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 2

3. Time schedule (Lectures) 8-99-1010-1111-1213-1414-1515-1616-17 Saturday Sunday Monday Tuesday Wednesday Thursday Friday 3

4. 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 … 4

5. 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

6. 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 6

7. 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! 7

8. 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

9. 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 9

10. 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. 10

11. Complex Systems Software Tools NetLogo Matlab – NN, GA, RBN Toolboxes Swarm Platform Conway's Game of Life 11