Towards reusable building blocks for agent-based modelling and theory development

被引:6
作者
Berger, Uta [1 ]
Bell, Andrew [2 ]
Barton, C. Michael [3 ,4 ]
Chappin, Emile [5 ]
Dressler, Gunnar [18 ]
Filatova, Tatiana [5 ]
Fronville, Thibault [10 ]
Lee, Allen [3 ,4 ]
van Loon, Emiel [6 ]
Lorscheid, Iris [7 ]
Meyer, Matthias [8 ]
Mueller, Birgit [18 ,20 ,21 ]
Piou, Cyril [9 ]
Radchuk, Viktoriia [10 ]
Roxburgh, Nicholas [11 ]
Schueller, Lennart [12 ]
Troost, Christian [13 ]
Wijermans, Nanda [14 ,15 ,16 ]
Williams, Tim G. [17 ]
Wimmler, Marie-Christin [1 ]
Grimm, Volker [18 ,19 ]
机构
[1] Tech Univ Dresden, Inst Forest Growth & Comp Sci, D-01062 Dresden, Germany
[2] Boston Univ, Boston, MA USA
[3] Arizona State Univ, Sch Human Evolut & Social Change, Tempe, AZ USA
[4] Arizona State Univ, Sch Human Evolut & Social Change, Tempe, AZ USA
[5] Delft Univ Technol, Dept Multiactor Syst, Fac Technol Policy & Management, Delft, Netherlands
[6] Univ Amsterdam, Amsterdam, Netherlands
[7] Univ Europe Appl Sci, Hamburg, Germany
[8] Hamburg Univ Technol, Hamburg, Germany
[9] Univ Montpellier, Inst Agro, CIRAD, UMR CBGP,INRAE,IRD, F-34398 Montpellier, France
[10] Leibniz Inst Zoo & Wildlife Res, Ecol Dynam Dept, Berlin, Germany
[11] James Hutton Inst, Aberdeen AB15 8QH, Scotland
[12] UFZ Helmholtz Ctr Environm Res, Dept Monitoring & Explorat Technol, Res Data Management, Dept Computat Hydrosyst, Leipzig, Germany
[13] Univ Hohenheim, Dept Land Use Econ 490d, Stuttgart, Germany
[14] Stockholm Univ, Stockholm Resilience Ctr, Stockholm, Sweden
[15] Stockholm Univ, Stockholm, Sweden
[16] Inst Future Studies, Stockholm, Sweden
[17] VU Univ Amstedam, IVM Inst Environm Studies, Environm Geog Grp, Amsterdam, Netherlands
[18] UFZ Helmholtz Ctr Environm Res, Dept Ecol Modelling, Leipzig, Germany
[19] Univ Potsdam, Dept Plant Ecol & Nat Conservat, Potsdam, Germany
[20] Brandenburg Univ Technol Cottbus Senftenberg, Modelling Human Environm Syst, Leipzig, Germany
[21] Idiv German Ctr Integrat Biodivers Res Halle Jena, Leipzig, Germany
关键词
Individual-based modelling; Theory development; Complex adaptive systems; Software engineering; Best practices; ASYMMETRIC FACILITATION; SIMULATION-MODEL; DECISION-MAKING; COMPETITION; DYNAMICS; PROTOCOL; DENSITY; PATTERN; PLANTS;
D O I
10.1016/j.envsoft.2024.106003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Despite the increasing use of standards for documenting and testing agent -based models (ABMs) and sharing of open access code, most ABMs are still developed from scratch. This is not only inefficient, but also leads to ad hoc and often inconsistent implementations of the same theories in computational code and delays progress in the exploration of the functioning of complex social -ecological systems (SES). We argue that reusable building blocks (RBBs) known from professional software development can mitigate these issues. An RBB is a submodel that represents a particular mechanism or process that is relevant across many ABMs in an application domain, such as plant competition in vegetation models, or reinforcement learning in a behavioural model. RBBs need to be distinguished from modules, which represent entire subsystems and include more than one mechanism and process. While linking modules faces the same challenges as integrating different models in general, RBBs are "atomic" enough to be more easily re -used in different contexts. We describe and provide examples from different domains for how and why building blocks are used in software development, and the benefits of doing so for the ABM community and to individual modellers. We propose a template to guide the development and publication of RBBs and provide example RBBs that use this template. Most importantly, we propose and initiate a strategy for community -based development, sharing and use of RBBs. Individual modellers can have a much greater impact in their field with an RBB than with a single paper, while the community will benefit from increased coherence, facilitating the development of theory for both the behaviour of agents and the systems they form. We invite peers to upload and share their RBBs via our website - preferably referenced by a DOI (digital object
引用
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页数:12
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