Teaching materials for students of the Simulating and analyzing complex social systems course at Jagiellonian University
This course introduces a social component into the formal analysis. We work with data, models and algorithms which describe human behaviour. By definition non-deterministic, heterogeneic and adaptive - this is core element common to all the addressed problems.
Understanding how a single human behaves is already a challenge, understanding how people (family, group, society, nation, etc.) behaves is even more challenging, when information, perception, learning and adaptation kick-in the system becomes truly complex. Importantly here we do not take the perspective of social sciences - this course is intended for mathematicians, physics, data scientists, AI/ML engineers and computer scientists (BA/MA/PhD students) - thus we always rely on hard empirical (big) data, statistical models, verified theories and frameworks.
- lecture (every week 1.5h)
- excercises (1.5h/week in the first half of the semester)
- project (ca 20h of work - in pairs, second half of the semester).
- few of the topics will be covered by me
- others - most (ca 10 will be covered by us: students and me).
- we will have 15 papers/articles/documents and each of them will be presented by one/two selected student and we will discuss them during classes
- for the first half of the semester we meet every week to introduce significant methods and libraries in python (ca.6 weeks)
- some excercises introduces a new python library(ies)
- some excercise is accompanied with a reprodubicle jupyter notebook with the code showing main functionalities and concepts
In the second half of the semest we will share the list of projects (in pairs) which you will work on, consult with us and present by the end of the semester
To pass the course you need to:
- be present at the lectures (two absences max)
- be present at the excercises (two absences max)
- at the lectures you need to prepare and present one topic (subject to availability) and actively participate in the group discussions
- present the group project and meet the objectives
Exam TBA - will be made during presentation of your projects. Me and the excercies tutor will jointly evaluate your project and discuss your knowledge from the lectures. The exam takes an oral form and we jointly grade you project (50%) and knowledge from lectures (50%). Extra points can be collected from the active participation in the discussions and excercises.
Course materials here
details in course.ipynb
- 04 III 25 - 1: Introduction + 101
- 11 III 25 - 2: Complex (Adaptive) Systems - XX
- 18 III 25 - 3: Modelling flow of pedestrians - Crowd Dynamics -
- 25 III 25 - 4: Game-theory and politics - Cuban Missile Crisis -
- 01 IV 25 - 5: Discrete choice models -
- 08 IV 25 - 6: Predicting our death with ML - Life2Vec
- 15 IV 25 - 7: Democracy and Theory of Voting -
- 29 IV 25 - 8: Networks -
- 06 V 25 - 9: Behavioural profiling - a.k.a. Cambridge analytica
- 13 V 25 - 10: Virus spreading - dynamics of Covid pandemics.
- 20 V 25 - 11: Recommendation systems - Youtube/TikTok/Instagram
- 27 V 25 - 12: News and Fakenews - Social networks
- 03 VI 25 - 13: Travel demand models.
- 10 VI 25 - 14: Platform revolution - Uber, AirBnB etc.
- extra one - 15: Human vs AI -
- 12 III 25 - Graphs: OSMnx, OTP, GTFS - AP
- 19 III 25 - Discrete Choice Models: Biogeme (examples), excel - OA
- 26 III 25 - Network science: Social Networks data, networkx - OA
- 02 IV 25 - Flow models: IDM, Pedestrian model - AP
- 9 IV 25 - RL: Essentials and MARL - OA & AP
- 16 IV 25 - Complex Systems: pyCX, Schelling's model of segregation - AP
- 23 IV 25 - Consultations
- 30 IV 25 - Consultations
- 07 V 25 - Consultations
- 14 V 25 - Consultations
- 21 V 25 - Consultations
- 28 V 25 - Consultations
- 04 VI 25 - Consultations
- 11 VI 25 - Consultations