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Syllabus for

Academic year
FFR120 - Simulation of complex systems
 
Syllabus adopted 2011-02-22 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

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

Examiner:

Professor  Martin Nilsson Jacobi


Course evaluation:

http://document.chalmers.se/doc/50ba31d7-f056-4ebd-a7bf-f96120cd3ab6


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 successfully completing this course the students will be able to
1) Define the fundamental ideas behind the simulation methods discussed in the course, e.g., agent based modelling and networks. 2) Implement simulation codes in the simulation methods. 3) Analyze and write short reports on results from a simulation. 4) Plan, manage, execute, and report a small-scale technical simulation project.

Content

1) Agent based models: swarm behavior, traffic simulations, social insects, social systems. 2) Game theory 3) Networks, random networks, small world networks, and scale free networks.

Organisation

The course is based on a series of lectures covering the topics listed above. 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: Thu 03 Nov 2022.