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.

基于代理的建模和仿真（ABMS）范例已用于分析，重现和预测与许多应用领域有关的现象。尽管有许多基于代理的平台支持仿真开发，但它们依赖于需要广泛编程知识的编程语言。已经探索了模型驱动的开发（MDD），以通过高级建模语言来促进仿真建模，该高级建模语言提供了可重用的构建块，从而隐藏了计算复杂性和代码生成。但是，关于MDD应用于ABMS的方法如何有助于提高开发效率和质量的知识仍然有限。因此，我们在本文中进行了一项实证研究，主要从工作量和开发人员错误方面定量比较了MDD和ABMS平台的使用。我们的评估是使用MDD4ABMS（一种具有核心功能并扩展到两个应用领域，其中一个是为该研究开发的）的MDD方法，以及NetLogo（一个广泛使用的平台）进行的。获得的结果表明，与NetLogo相比，MDD4ABMS可以用更少的精力来开发具有类似（有时更好）设计质量的仿真，这证明了MDD可以为ABMS提供好处。