Using Agent-Based Modeling to Understand Complex Social Phenomena: A Curriculum Approach

André Calero Valdez*, Johannes Nakayama, Luisa Vervier, Hendrik Nunner, Martina Ziefle

*Corresponding author for this work


Agent-based modeling (ABM) is a powerful tool for studying complex systems that involve multiple agents interacting with each other and their environment. However, there is a lack of comprehensive and easily accessible resources for learning about ABM and its applications. To address this issue, collaboration on developing an open curriculum on ABM for university seminars is proposed. An open curriculum would allow for the sharing of expertise and knowledge across disciplines and institutions, be more accessible to a broader audience, and foster greater collaboration and cooperation among researchers and practitioners in the field of ABM. This would ultimately improve the accessibility and impact of ABM as a tool for understanding and predicting the behavior of complex systems. We propose a curriculum comprising six modules covering the introduction to ABM, building an ABM, analyzing and interpreting results, real-world applications, advanced topics, and future directions.

Original languageEnglish
Title of host publication14th International Conference Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, DHM 2023, held as part of the 25th International Conference on Human-Computer Interaction, HCII 2023 : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Nature Swiitzerland
Publication date2023
Pages368 - 377
Publication statusPublished - 2023

Coronavirus related work

  • Research on SARS-CoV-2 / COVID-19


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