This work discusses the benefits of having multiple simulated environments with different degrees of realism for the development of algorithms in scenarios populated by autonomous nodes capable of communication and mobility. This approach aids the development experience and generates robust algorithms. It also proposes GrADyS-SIM NextGen as a solution that enables development on a single programming language and toolset over multiple environments with varying levels of realism. Finally, we illustrate the usefulness of this approach with a toy problem that makes use of the simulation framework, taking advantage of the proposed environments to iteratively develop a robust solution.

翻译：本文探讨了在由具备通信与移动能力的自治节点构成的场景中，采用多种不同真实度仿真环境对算法开发的益处。该方法有助于提升开发体验，并生成鲁棒性更强的算法。同时，本文提出了GrADyS-SIM NextGen作为解决方案，支持在单一编程语言和工具集上跨越多种不同真实度环境进行开发。最后，我们通过一个利用该仿真框架的示例问题，展示了该方法的实用性，并借助所提出的环境迭代开发出鲁棒性解决方案。