COMPLEX SYSTEMS

Course Information
TitleΠΟΛΥΠΛΟΚΑ ΣΥΣΤΗΜΑΤΑ / COMPLEX SYSTEMS
CodeIW-02
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorKonstantinos(constantine) Kotropoulos
CommonNo
StatusActive
Course ID600000813

Programme of Study: PPS School of Informatics (2014-today)

Registered students: 2
OrientationAttendance TypeSemesterYearECTS
TECΗNOLOGIES GNŌSĪS DEDOMENŌN KAI LOGISMIKOUElective Courses117.5
TECΗNOLOGIES PLĪROFORIAS KAI EPIKOINŌNIŌN STĪN EKPAIDEUSĪElective Courses117.5
PSĪFIAKA MESA- YPOLOGISTIKĪ NOĪMOSYNĪElective Courses belonging to the selected specialization117.5
DIKTYAKA SYSTĪMATAElective Courses117.5

Class Information
Academic Year2015 – 2016
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600011402
Type of the Course
  • Scientific Area
  • Skills Development
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
General Prerequisites
Prior exposition to linear algebra and numerical optimization facilitates to grasp faster the concepts introduced.
Learning Outcomes
1) Το get acquainted with computational models of complex adaptive systems of social life 2) To learn in depth diffusion strategies in adaptive systems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Generate new research ideas
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
1. Complexity in social world 2. Models of complex adaptive social systems 3. Social dynamics 4. Evolving automata 5. Diffusion adaptation in Complex Systems • Mean-Square-Error estimation • Distributed optimization via diffusion strategies • Adaptive diffusion strategies • Performance of steepest-descent diffusion strategies • Performance of adaptive diffusion strategies • Diffusion with noisy information exchanges 6. Mobile adaptive networks 7. Social learning and Bayesian games in multiagent signal processing 8. Consensus+ιnnovations distributed inference over networks 9. Applications to distributed music classification
Keywords
complex systems, adaptive techniques, diffusion strategies
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures1053.5
Reading Assigment301
Project602
Written assigments150.5
Exams150.5
Total2257.5
Student Assessment
Description
The written exams contribute to the final grade by 50%. Homework and projects contribute to the final grade by 40%. The active participation to the class lectures gives the remaining 10% of the final grade.
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Performance / Staging (Formative, Summative)
Bibliography
Additional bibliography for study
1) J. H. Miller and S. E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton Univ. Press. 2007. 2) A. H. Sayed, Adaptation, Learning, and Optimization over Networks, Foundations and Trends in Machine Learning, vol. 7, issue 4-5, NOW Publishers, Boston-Delft, 518pp, 2014. ISBN 978-1-60198-850-8, DOI 10.1561/2200000051. 3) A. H. Sayed, Adaptive Filters, John Wiley & Sons, NJ, ISBN 978-0-470-25388-5, xxx+786pp, 2008. 4) Special Issue Adaptation and Learning over Complex Networks, IEEE Signal Processing Magazine, vol. 30, no. 3, May 2013.
Last Update
15-02-2016