ECTS Informacijski paket za akademsku godinu 2021. / 2022.

Modelling in Social Sciences

 

Naziv
Modelling in Social Sciences
Organizacijska jedinica
Odsjek za sociologiju
ECTS
6
Šifra
215554
Semestri
ljetni
Nastavnici
Satnica
Predavanja
30
Seminar
30

Cilj
The course deals with basic theoretical assumptions, purpose and attributes of crucial approaches in the construction of simulation models, as recently a quite propulsive, primarily interdisciplinary, knowledge field emerged due to the vigorous advancement of computer technologies. It examines the advantages and prospects of social simulation methodology and unfolds it shortcomings and constraints. Particular emphasis is on the question whether (and to which degree) simulation models can elevate the explanatory and predictive power of social sciences (especially sociology), but also how they can be practically applied in order to foster certain social processes. The content of the instruction comprises scrutinizing the central features of the following types of modelling: system dynamics, microsimulations, discrete models, multilevel modelling, cellular automata, agent-based modelling, neural networks, expert systems, etc. Moreover, the course discusses in which manner artificial intelligence (as a specific type of model) can be integrated into diverse domains of social life nowadays.
Sadržaj
  1. Overview of the Course /Assigning the Seminar Tasks
  2. ‘Three Waves of Systems Theory in Sociology’
  3. ‘Simulation as the Sociological Method’
  4. ‘System Dynamics’
  5. ‘Discrete Event Simulation’
  6. ‘Microsimulations’
  7. ‘Cellular Automata’
  8. ‘Multi-agent Systems’
  9. ‘Artificial Intelligence 1’
  10. ‘Artificial Intelligence 2'
  11. ‘Artificial Intelligence 3'
  12. 'Visit to Simulation Centre of Croatian Military Forces'
  13. ‘Guest Lecture 1'
  14. ‘Guest Lecture 2’
  15. Concluding Discussion / Review for Final Examination / Guidelines for a Paper Development

Ishodi učenja
  1. Writing and competently discussing the review paper on a chosen topic concerning modelling in social sciences
  2. Analyzing and critically evaluating perspectives of development and application of simulation models in social sciences (particularly in sociology)
  3. Using and critically examining concepts within a given topic field
  4. Developing, at the conceptual level, an original simulation model
  5. Acquiring competencies for teamwork in an interdisciplinary knowledge field
Metode podučavanja
Method of lecture, dialogue, discussion, oral and visual presentation (PowerPoint), consultations with students and even individual lessons if it is necessary. Current technological and electronic devices will be applied during lessons. The lectures will be held on-line.
Metode ocjenjivanja
class attendance; seminar paper/oral presentation; writing homework assignments; final written paper that is additionally discussed on an oral exam or, alternatively, written exam, which will be held in a format of oral examination if conducted on-line
Standard – the institutional grading system (5 Excellent; 4 Very good; 3 Good; 2 Sufficient; 1 Fail)
C+ / Completed + ECTS (Student has completed prescribed obligations + ECTS credits awarded)

Obavezna literatura
  1. Hartmann, S. (1996). The World as a Process. Simulations in the Natural and Social Sciences, In: Hegselmann, R., Mueller, U., Troitzsch, K. G. (eds.) Modelling and Simulation in the Social Sciences from the Philosophical Point of View. Dordrecht / Boston / London: Kluwer Academic Publishers. (pp. 77-100).
  2. Hegselmann, R. (1996). Cellular Automata in the Social Sciences. Perspectives, Restrictions, and Artefacts, In: Hegselmann, R., Mueller, U., Troitzsch, K. G. (eds.) Modelling and Simulation in the Social Sciences from the Philosophical point of View. Dordrecht – Boston – London: Kluwer Academic Publishers. (pp. 209-233)
  3. Klein, D., Marx, J., Fischbach, K. (2018). Agent-Based Modeling in Social Science, History, and Philosophy: An Introduction. Historical Social Research / Historische Sozialforschung, 43(1):7-27.
  4. Russel, S., Norvig, P. (2010). Artificial Intelligence: A Modern Approach. Prentice Hall. (3rd Edition) (pp. 1-33)
  5. Sawyer, R. K. (2005). Social Emergence, Societies as Complex Systems. Cambridge: University Press.
Dopunska literatura
  1. Buckley, W. F. (1968). Modern Systems Research for the Behavioral Scientist: A Sourcebook. Aldine Pub. Co, Chicago (Part I: General Systems Research: Overview)
  2. Davidsson, P., Verhagen, M. (2017). ‘Types of Simulation’, In: B. Edmonds, R. Meyer (eds.) Simulating Social Complexity (Second Edition). Springer. (pp. 23-37)
  3. Squazzoni, F., Polhill, J. G., Edmonds, B., Ahrweiler, P., Antosz, P., Scholz, G., Chappin, E., Borit, M., Verhagen, H., Giardini, F., & Gilbert, N. (2020). Computational models that matter during a global pandemic outbreak: A call to action. Journal of Artificial Societies and Social Simulation, 23(2), 10: http://jasss.soc.surrey.ac.uk/23/3/10.html. [doi:10.18564/jasss.4298]
  4. Struben, J. (2020). The coronavirus disease (COVID-19) pandemic: Simulation-based assessment of outbreak responses and post peak strategies. System Dynamics Review, 36(3), 247-293. [doi:10.1101/2020.04.13.20063610]
  5. Badham, J., Barbrook-Johnson, P., Caiado, C., Castellani, B. (2021). Justified Stories with Agent-Based Modelling for Local COVID-19 Planning. Journal of Artificial Societies and Social Simulation 24 (1) 8. http://jasss.soc.surrey.ac.uk/24/1/8.html DOI: 10.18564/jasss.4532
  6. Mahmood, I., Arabnejad, H., Suleimenova, D., Sassoon, I., Marshan, A., Serrano-Rico, A., Louvieris, P., Anagnostou, A., Taylor, S. J. E., Bell, D., & Groen, D. (2020). FACS: A geospatial agent-based simulator for analysing COVID-19 spread and public health measures on local regions. Journal of Simulation, 1–19. [doi:10.1080/17477778.2020.1800422]
  7. Brown, L., Harding, A. (2002). Social Modelling and Public Policy: Application of Microsimulation Modelling in Australia. Journal of Artificial Societies and Social Simulation vol. 5, no. 4 http://jasss.soc.surrey.ac.uk/5/4/6.html
  8. Sallila, S. (2010). Using Microsimulation to Optimize an Income Transfer System Towards Poverty Reduction. Journal of Artificial Societies and Social Simulation 13 (1) 1. http://jasss.soc.surrey.ac.uk/13/1/1.html DOI
  9. Beltran, F. S., Herrando, S., Ferreres, D., Adell, M.-A., Estreder, V., Ruiz-Soler, M. (2009). Forecasting a Language Shift Based on Cellular Automata. Journal of Artificial Societies and Social Simulation 12 (3) 5. http://jasss.soc.surrey.ac.uk/12/3/5.html
  10. McPhee-Knowles, S. (2015). Growing Food Safety from the Bottom Up: An Agent-Based Model of Food Safety Inspections. Journal of Artificial Societies and Social Simulation 18 (2) 9 http://jasss.soc.surrey.ac.uk/18/2/9.html
  11. Boden, M. A. (2014). Creativity and artificial intelligence. The Philosophy of Creativity. Oxford University Press, New York, NY: 224-244.

Izborni kolegij na studijima
  1. Sociologija, sveučilišni diplomski jednopredmetni studij
  2. Sociologija, sveučilišni diplomski dvopredmetni studij
Fakultetska ponuda
  • Diplomski studij: Ljetni semestar