Course Catalog 2007-2008

SGN-6457 COMPUTATIONAL MODELS IN COMPLEX SYSTEMS, 5 cr
Computational Models in Complex Systems

Courses persons responsible
Olli Yli-Harja

Lecturers
Juha Kesseli

Objectives
Introduce a large amount of examples, models, and concepts in complex systems. Introduce mathematical tools and methods that are used in complex systems. Practice programming of models with a programming language (Matlab). After the course the student: a) Knows what kind of scientific methods are available for complex systems b) Knows the basic properties of these methods c) Is able to code a simple method or a model d) Is able to analyze the results. Prepare the student for the other Complex Sytems courses.

Content
Content Core content Complementary knowledge Specialist knowledge
1. Mathematical methods in Complex systems:
Algorithmic complexity,
Fractals,
Non-linear dynamics,
Chaos theory,
Cellular automata,
Power laws,
Self-organized criticality,
Complex networks,
Evolution,
Genetic algorithms,
Pattern formation,
Synchronization phenomena,
Game theory,
Autonomous agents,
Artificial life. 		      
2. Programming models of complex systems:
Matlab,
Netlogo. 		      
3. Systemic view on solving complex problems.       

Requirements for completing the course
Written examination and computer exercises (min. 50%)

Evaluation criteria for the course

  • Examination. Students may earn extra points for the exam with computer exercises.

  • Used assessment scale is numeric (1-5)

    • Study material
    Type Name Auhor ISBN URL Edition, availability... Exam material Language
    Lecture slides Computational Models for Complex Systems Juha Kesseli       Yes  English 

    Prerequisites
    Prequisite relations (Sign up to TUT Intranet required)

    Additional information about prerequisites
    Basic mathematics courses passed.

    Remarks

  • The course is suitable for postgraduate studies.

  • Course will not be lectured in the academic year 2007-2008.

    • Distance learning

  • ITC utilized during the course

    • - In information distribution via homepage, newsgroups or mailing lists, e.g. current issues, timetables
    - In distributing and/or returning exercise work, material etc

  • Estimate as a percentage of the implementation of the course

    • - Contact teaching: 35 %
    - Distance learning: 0 %
    - Proportion of a student's independent study: 65 %

  • Description of the course implementation from ICT point of view

    • 50% of the laboratory exercises are mandatory. Lectures are not mandatory. Exam consists of 6 question of which some are essays.

    Scaling
    Methods of instructionHours
    Lectures 36
    Exercises 72
    Total sum 108

    Principles and starting points related to the instruction and learning of the course

  • Lecture teaching is intensive and the teacher explains every topic with the blackboard and slides. Computer exercises allow more student-teacher interaction. Students prepare the given exercises with a computer and the teacher is always present to help if needed. Students may also present questions that are related to the lecture topics.

    • Additional information related to course
    Complexity arises in situations where the system parts (or agents) interact with each other in a complicated "emergent" fashion. Complex Systems is a highly multidisciplinary research topic that aims to understand complex behaviour and solve practical problems that arise in numerous different situations. This course introduces mathematical tools and concepts that are widely used in the complex systems community.

    Correspondence of content
    SGN-6456 Computational Models in Complex Systems

    Last modified 05.09.2007
    Modified byVirpi Hämäläinen