- Docente: Mario Paolucci
- Credits: 8
- SSD: INF/01
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Digital Innovation Policies and Governance (cod. 5889)
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from Feb 18, 2025 to May 06, 2025
Learning outcomes
The course aims to provide the foundations of methodologies and tools for designing, implementing, and validating simulation models for the analysis and evaluation of complex social systems. By the end of the course, the student will be capable of designing, implementing, and validating simulation models by adopting the most suitable technologies for analyzing the specific problem. Additionally, the student will be able to apply the acquired knowledge to solve simulation problems of various natures, using appropriately specialized software tools for the cases of interest.
Course contents
The course in Methodologies and Techniques of Simulation offers students an in-depth experience in the field of agent-based simulation, a powerful modeling methodology for exploring complex and dynamic systems. The main objective is to equip students with the necessary skills to design, implement, and interpret agent-based simulations using one of the key platforms: NetLogo and Mesa (Python).
The course will introduce students to the practice of reading and commenting on simulations published in selected scientific articles. This aspect will provide a realistic perspective on the application of agent-based simulations in real-world research and problem-solving contexts. Students will be guided in the critical analysis of these simulations, identifying design choices, and interpreting results.
Readings/Bibliography
- Gilbert, N. and Troitzsch, K. G. Simulation for the Social Scientist, 2nd edition. Buckingham: Open University Press, 2005.
-Axtell, R. Why agents? on the varied motivations for agent computing in the social sciences. In Working Paper 17,Center on Social and Economic Dynamics, Brookings Institution, volume 17, 2000.
- Conte, R., Paolucci, M. On Agent Based Modelling and Computational Social Science (2011). http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1876517Teaching methods
Lectures (both in presence and online), practical exercises, readings, and presentations of scientific articles.
Assessment methods
To be presented during the course.
Teaching tools
L'insegnamento partecipa al progetto di sperimentazione didattica dell'Ateneo
Office hours
See the website of Mario Paolucci
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.