A Guide to Re-Implementing Agent-based Models: Experiences from the HUMAT Model

Gürcan, Önder, Szczepanska, Timo, Antosz, Patrycja

arXiv.org Artificial Intelligence 

Replicating existing agent-based models poses significant challenges, particularly for those new to the field. This article presents an all-encompassing guide to re-implementing agent-based models, encompassing vital concepts such as comprehending the original model, utilizing agent-based modeling frameworks, simulation design, model validation, and more. By embracing the proposed guide, researchers and practitioners can gain a profound understanding of the entire re-implementation process, resulting in heightened accuracy and reliability of simulations for complex systems. Furthermore, this article showcases the re-implementation of the HUMAT socio-cognitive architecture, with a specific focus on designing a versatile, language-independent model. The encountered challenges and pitfalls in the re-implementation process are thoroughly discussed, empowering readers with practical insights. Embrace this guide to expedite model development while ensuring robust and precise simulations.

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