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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
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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
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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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