Previous evolutionary studies demonstrated how robust solutions can be obtained by evaluating agents multiple times in variable environmental conditions. Here we demonstrate how agents evolved in environments that vary across generations outperform agents evolved in environments that remain fixed. Moreover, we demonstrate that best performance is obtained when the environment varies at a moderate rate across generations, that is, when the environment does not vary every generation but every N generations. The advantage of exposing evolving agents to environments that vary across generations at a moderate rate is due, at least in part, to the fact that this condition maximizes the retention of changes that alter the behavior of the agents, which in turn facilitates the discovery of better solutions. Finally, we demonstrate that moderate environmental variations are advantageous also from an evolutionary computation perspective, that is, from the perspective of maximizing the performance that can be achieved within a limited computational budget.

中文翻译：

---

跨代的适度环境变化促进了稳健解决方案的发展

先前的进化研究证明了如何通过在可变环境条件下多次评估代理来获得稳健的解决方案。在这里，我们展示了代理如何在不同代的环境中进化，其性能优于在保持固定的环境中进化的代理。此外，我们证明了当环境在几代之间以中等速度变化时，即当环境不是每一代而是每 N 代都改变时，可以获得最佳性能。将不断进化的智能体暴露在以中等速度变化的环境中的优势，至少部分是由于这种条件最大限度地保留了改变智能体行为的变化，这反过来又促进了发现更好的解决方案。最后，