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Agent-Based Modelling in Population Studies

Concepts, Methods, and Applications

Jezik EngleskiEngleski
Knjiga Tvrdi uvez
Knjiga Agent-Based Modelling in Population Studies André Grow
Libristo kod: 02961338
Nakladnici Springer International Publishing AG, kolovoz 2016
This book examines the use of agent-based modelling (ABM) in population studies, from concepts to ap... Cijeli opis
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This book examines the use of agent-based modelling (ABM) in population studies, from concepts to applications, best practices to future developments. It features papers written by leading experts in the field that will help readers to better understand the usefulness of ABM for forecasting, how ABM can be injected with empirical data to achieve a better match between model and reality, how geographic information can be fruitfully used in ABM, and how ABM results can effectively and correctly be reported in a concise way. § Overall, coverage ranges from detailing methods of agent-based modelling to existing paradigms in population studies to infusing agent-based models with empirical data. The papers show the benefits that ABM offers the field, such as enhanced theory formation by better linking the micro-level with the macro-level, the ability to represent populations more adequately as complex systems, and a way that laboratories can study rare events and the implications of alternative mechanisms. § In addition, readers will discover guidelines and best-practices with detailed examples of how to apply agent-based models in different areas of population research, including human mating behaviour, migration, and socio-structural determinants of health behaviours. § This book collects papers from the workshop "Recent Developments and Future Directions in Agent-Based Modelling in Population Studies," which took place at the University of Leuven, Belgium in September 2014. It will contribute to the development of best-practices in the field and will provide a solid point of reference for scholars who want to start using agent-based modelling in their own research.

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