Il Corso

Questo corso introduce la modellazione basata su agenti (Agent-based Modeling) come metodologia per l’indagine sociale e la ricerca politica.

Il corso sarà tenuto in lingua inglese

This course introduces agent-based modeling (ABM) as a methodology for social inquiry and policy research. This method allows to tackle the dynamics of social phenomena through the formalization of mechanisms of interaction and collective action. Virtual agents in artificial societies mimic the characteristics, beliefs and intentions of human beings, as well as social institutions, operating according to behavioural rules that can be theory-driven or empirically grounded. The contribution of the method is to analytically investigate how micro-level behaviours and interactions generate macro-level observable outcomes, by systematically manipulating the conditions under which social interactions occur. Synthetic populations are a set of techniques to ensure that artificial societies replicate the statistical properties of the target population, which is relevant when the method is used for policy testing. The course will show the cycle of research with ABM and tools available. Special attention will be devoted to the application of the method and synthetic populations to policy design.

Relatore

Rocco Paolillo (CNR-IRPPS)

Short Bio

Rocco Paolillo is a researcher at the Institute for Population and Social Policies (IRPPS), as part of the NRPP project Fostering Open Science in Social Science Research (FOSSR). His work involves the development and distribution of algorithms for the extraction of synthetic populations to apply in social science and policy research. His further research interests include the application of computational methods such as social simulation and text-analysis to study social phenomena such as social integration and public opinion.

Come partecipare

Il corso è online e aperto al pubblico previa registrazione attraverso questo modulo.

Comitato organizzatore

Tommaso Ismaelli, Andrea Giovanni Nuzzolese.

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