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Syllabus for

Academic year
FFR120 - Simulation of complex systems
 
Syllabus adopted 2013-02-20 by Head of Programme (or corresponding)
Owner: MPCAS
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Engineering Physics
Department: 16 - PHYSICS


Teaching language: English
Open for exchange students
Block schedule: D

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0199 Project 7,5 c Grading: TH   7,5 c    

In programs

MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (compulsory)
MPSYS SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (elective)

Examiner:

Professor  Martin Nilsson Jacobi


Course evaluation:

http://document.chalmers.se/doc/6fff4e88-8b49-445e-b3e0-1d044082e01b


Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

The students are expected to have a background in natural science corresponding to an undergraduate education in mathematics, computer science, physics, chemistry, or biology. Furthermore, the students are expected to have programming experience in C, C++, Pascal, Matlab, or some other equivalent language.

Aim

The course introduces the students to three simulation techniques frequently used in complex systems: agent based modelling, networks, and cellular automata. Examples of applications in physics, biology and social science, are discussed. The aim of the course is to give the students a level of understanding for the three methods such that they can decide which method is suited for a specific problem, define and implement a moderate sized simulation project, and evaluate the results from their simulations.

Learning outcomes (after completion of the course the student should be able to)

After this course you will be able to
-Describe the fundamental ideas behind the three simulation methods discussed in the course, i.e., agent based modeling, networks, and cellular automata
-Implement simulation codes in each of the methods
-Analyze and discuss the results of simulations
-Plan, manage, execute and report a small-scale simulation project

Content

Much of modeling in the sciences focuses on simple models, highlighting key mechanisms using small sets of moving parts. However, in complex systems the interesting features are often a direct result of having large sets of particles or agents with different characteristics. This makes new tools a necessity.
The course introduces three simulation techniques frequently used in complex systems to handle models with many heterogeneous parts: agent-based modeling, networks, and cellular automata. For each technique we discuss its background, where its strengths and weaknesses lie, and study some examples in physics, biology and social science.
The course is comprised of: 1) a set of lectures, giving background and basics of the simulation techniques; 2) computer labs, giving hands-on experience of the techniques and of analyzing models; and 3) a group project, training problem formulation, project work, and going more in-depth on a topic.

Organisation

The course is based on a series of lectures covering the various topics. The students work on simulation projects in groups of two to four students. A tutor supervises each group. Complementary to the lectures there are supervised computer labs where the students solve a variety of small simulation tasks (some of which should also be reported as home assignments).

Literature

Handouts of shorter texts and articles related to the subjects discussed at the lectures.

Examination

The examination is based on
Homework assignments
Projects (oral presentation and written report)


Page manager Published: Mon 28 Nov 2016.