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Introduction to agent-based modelling for social scientists
Social science seeks to understand and predict patterns involving human behaviour, many of which are large-scale and complex. But social science explanations or predictions can be difficult to test and refine because of the serious ethical and practical barriers to running experiments on the real world! For example, there are many possible explanations for the complex patterns of urban mobility, but when traffic calming measures fail to produce the desired results it can be difficult to identify why or how the situation can be improved. One possible solution is to run social science experiments 'in silico' via an agent-based model (ABM) in which simulated actors have features, behaviours and actions informed by real world data. Such ABM experiments allow social scientists to test and refine their understanding of problems and possible solutions and to explore how emergent patterns might change under alternative conditions.

This free webinar, organised by the UK Data Service, is the first in a training series on how to use agent-based models combined with real world data to address social science questions.

The UK Data Service will only use the personal information you provide for this event, unless you tell us you wish us to use it for other purposes (such as keeping you up-to-date about our events or contacting you regarding feedback on our services), and will store that data for a maximum of 3 months after the event. After this period, we will retain only anonymised data for reporting purposes.

Jan 19, 2022 01:00 PM in London

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