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和移动能力的自主节点构成的场景中，采用不同真实度模拟环境对算法开发的益处。该方法不仅优化了开发体验，还能生成鲁棒性更强的算法。本文进一步提出GrADyS-SIM NextGen作为解决方案，允许在单一编程语言和工具集上跨越多个不同真实度环境进行开发。最后，通过一个利用该仿真框架的示例问题，展示了如何借助所提出的环境迭代开发鲁棒性解决方案，验证了该方法的实用性。