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Main Authors: Gürcan, Önder, Szczepanska, Timo, Antosz, Patrycja
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.03994
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author Gürcan, Önder
Szczepanska, Timo
Antosz, Patrycja
author_facet Gürcan, Önder
Szczepanska, Timo
Antosz, Patrycja
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2405_03994
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Guide to Re-Implementing Agent-based Models: Experiences from the HUMAT Model
Gürcan, Önder
Szczepanska, Timo
Antosz, Patrycja
Multiagent Systems
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.
title A Guide to Re-Implementing Agent-based Models: Experiences from the HUMAT Model
topic Multiagent Systems
url https://arxiv.org/abs/2405.03994