The agent-based modeling and simulation (ABMS) paradigm has been used to analyze, reproduce, and predict phenomena related to many application areas. Although there are many agent-based platforms that support simulation development, they rely on programming languages that require extensive programming knowledge. Model-driven development (MDD) has been explored to facilitate simulation modeling, by means of high-level modeling languages that provide reusable building blocks that hide computational complexity, and code generation. However, there is still limited knowledge of how MDD approaches to ABMS contribute to increasing development productivity and quality. We thus in this paper present an empirical study that quantitatively compares the use of MDD and ABMS platforms mainly in terms of effort and developer mistakes. Our evaluation was performed using MDD4ABMS-an MDD approach with a core and extensions to two application areas, one of which developed for this study-and NetLogo, a widely used platform. The obtained results show that MDD4ABMS requires less effort to develop simulations with similar (sometimes better) design quality than NetLogo, giving evidence of the benefits that MDD can provide to ABMS.

中文翻译：

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定量评估模型驱动开发在基于代理的建模和仿真中的优势

基于代理的建模和仿真 (ABMS) 范式已被用于分析、再现和预测与许多应用领域相关的现象。尽管有许多基于代理的平台支持模拟开发，但它们依赖于需要大量编程知识的编程语言。模型驱动开发 (MDD) 已被探索以促进仿真建模，通过高级建模语言提供隐藏计算复杂性和代码生成的可重用构建块。然而，对于 ABMS 的 MDD 方法如何有助于提高开发生产力和质量，仍然知之甚少。因此，我们在本文中提出了一项实证研究，主要在工作量和开发人员错误方面对 MDD 和 ABMS 平台的使用进行了定量比较。我们的评估是使用 MDD4ABMS（一种具有核心和扩展到两个应用领域的 MDD 方法，其中一个是为本研究开发的）和 NetLogo（一种广泛使用的平台）进行的。获得的结果表明，与 NetLogo 相比，MDD4ABMS 需要更少的努力来开发具有相似（有时更好）设计质量的模拟，这证明了 MDD 可以为 ABMS 提供的好处。