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ODD+2D: An ODD Based Protocol for Mapping Data to Empirical ABMs

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The quantity of data and processes used in modeling projects has been dramatically increasing in recent years due to the progress in computation capability and to the popularity of new approaches such as open data. Modelers face an increasing difficulty in analyzing and modeling complex systems that consist of many heterogeneous entities. Adapting existing models is relevant to avoid dealing with the complexity of writing and studying a new model from scratch. ODD (Overview, Design concepts, Details) protocol has emerged as a solution to document Agent-Based Models (ABMs). It appears to be a convenient solution to address significant problems such as comprehension, replication, and dissemination. However, it lacks a standard that formalizes the use of data in empirical models. This paper tackles this issue by proposing a set of rules that outline the use of empirical data inside an ABM. We call this new protocol ODD+2D (ODD+Decision + Data). ODD+2D integrates a mapping diagram called DAMap (Data to Agent Mapping). This mapping model formalizes how data are processed and mapped to agent-based models. In this paper, we focus on the architecture of ODD+2D, and we illustrate it with a residential mobility model in Marrakesh.

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  • Ahmed Laatabi & Nicolas Marilleau & Tri Nguyen-Huu & Hassan Hbid & Mohamed Ait Babram, 2018. "ODD+2D: An ODD Based Protocol for Mapping Data to Empirical ABMs," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(2), pages 1-9.
    • Handle: RePEc:jas:jasssj:2016-94-3
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    3. Anshuka Anshuka & Floris F. Ogtrop & David Sanderson & Simone Z. Leao, 2022. "A systematic review of agent-based model for flood risk management and assessment using the ODD protocol," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2739-2771, July.
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    6. Zanini, Sara, 2023. "Water challenges in socio-ecological systems: is human decision-making accounted for in the analysis of climate change adaptation options?," FEEM Working Papers 333364, Fondazione Eni Enrico Mattei (FEEM).
    7. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    8. Giacomo Ravaioli & Tiago Domingos & Ricardo F. M. Teixeira, 2023. "A Framework for Data-Driven Agent-Based Modelling of Agricultural Land Use," Land, MDPI, vol. 12(4), pages 1-17, March.

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