Complex System Simulation

Course manual 2024/2025

Course content

The course has two major components, the first two weeks will include lectures covering concepts and methods related to Complex System Simulation. The second two weeks will be group projects (2-3 students), where each group will develop a simulation of a complex system and conduct research using that simulation.

The group project should reflect the concepts and methods covered in the first two weeks, however students are also encouraged to self study and suggest alternative ideas.

Topics to be covered (preliminary, may change):

• Introduction to Complex Systems / Modelling and Simulation
• Introduction to Cellular Automata (1D/2D CA, rule codes,phenomenological studies, behaviour classes)
• Self-Organized Criticality (Sandpile Model, Forest fire model)
• Networks (giant component; cluster size distribution; Watts-Strogatz model)
• Deterministic chaos (lyapunov exponent; period doubling; stretching and folding)
• Measures of complexity (Kolmogorov complexity versus stochastic complexity)
• Phase Transitions (Landau theory, first and second order transitions) versus tipping points.

Study materials

Literature

• Nino Boccara: 'Modeling Complex Systems' (see also http://www.amazon.com/gp/product/0387404627/103-6032108-4445446)

• Mark Newman: 'Networks: An Introduction' (see also http://www.amazon.com/Networks-Introduction-Mark-Newman/dp/0199206651)
• Background material: Andrew Ilachinski, 'Cellular Automata: A Discrete Universe', World Scientific Publishing Co. Pte. Ltd., 2001.
• Laszlo Barabasi - 'Network Science' (see also http://barabasilab.neu.edu/networksciencebook/downlPDF.html)
• Advanced Physics Texts: Kim Christensen, Nicholas R. Moloney, 'Complexity and Criticality', Paperback, Imperial College Press, 2005

Objectives

• Explain the concept of emergence
• Name and reason about different types of emergent phenomena, such as chaos, phase transitions, network connectivity, and complexity
• Name and reason about different types of computational models used to study these phenomena
• Choose and implement an appropriate model to reproduce a given emergent phenomenon
• Compare numerical model outcomes with predictions from (mean-field) theory
• Interpret and use the model outcomes in terms of practical applications
• Implement and study interventions and what-if scenarios to improve/optimize with respect to a practical application

Teaching methods

• Lecture
• Working independently on e.g. a project or thesis
• Laptop seminar

During the lectures (first half of the course) the students will learn about a wide variety of theoretical concepts relevant to studying complex systems. This will be combined with independently reading provided materials. In the second half a selection of theory and methods will be used to perform a computational study by a project group, in laptop seminars as well as working independently.

Learning activities

Attendance

This programme does not have requirements concerning attendance (Ter part B).

Additional requirements for this course:

Although the lectures and laptop seminars are not formally listed as mandatory, they are treated as such, as complexity related concepts are difficult at first to grasp and to connect to each other (it is still a relatively young field). Questions on the Quiz may come from material discussed during the lectures.

Assessment

It is not necessary to pass (>= 5.5) on each individual grade in order to pass the course, only the final weighted average must pass (>= 5.5). Subgrades will not be rounded. However, a minimum of 4.0 grade for the theory quiz must be obtained in order to be allowed to proceed with the group project phase. The theory quiz is at the end of the second week and requires physical attendance. The resit for the theory quiz will be during the official resit week of UvA; please notify the coordinator if you intend to make use of the resit.

Inspection of assessed work

Contact the course coordinator to make an appointment for inspection.

Assignments

Project plan

• This is a pass/fail group assignment at the start of week 3 to kickstart the project phase. Feedback occurs in the first laptop seminar that follows, per group.

Project presentation

• Final presentation by the group.

Code and documentation

• Group assignment. The code must reproduce the figures used in the presentation. It must be stand-alone understandable with good structure, inline comments, and documentation.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Additional information

Programming (any language) and basic mathematics skills (probability theory; linear algebra; calculus) will be indispensable.

Contact information

Coordinator

• dr. Rick Quax