发表机构
University of Vermont（佛蒙特大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出一种机制，通过机器内部形态多样的主体构建群体，让物理连接器驯服内部干扰，提升群体应对新环境的适应性，为机器环境适应性设计提供思路。
AI 中文摘要
生物在不同尺寸尺度上拥有多样的感知运动部件，能快速适应新环境，而机器在更小尺度仅含惰性材料，难以应对意外情况。我们假设生物的“主体嵌套主体”特性可能有助于其适应性：增加内部物理逆境的体验，可预训练生物和机器以应对外部逆境，例如遭遇新环境。该假设尚未明确，也未提出实现此现象的机制。本文展示了一种可能的机制：物理连接器在学习恢复因束缚而被破坏的、原本独立且形态多样的主体的行为时，会触发并驯服足够多样的干扰，使后续新环境遭遇的干扰落入可管理范围，让群体无需额外学习或适应即可正常运行。此外，我们发现由更多主体或更多样主体构建的群体，对新环境的适应性进一步提升。这表明，不仅是驯服，刻意创造内部物理逆境确实可让生物为外部逆境做好准备，若机器由更小的机器构建，也能实现这一点。
英文摘要
Organisms contain diverse, sensorimotor parts across size scales and rapidly adapt to new environments, while machines contain only inert materials at smaller scales and struggle with surprise. We hypothesize that this agents-within-agents quality of organisms may aid their resilience: increasing experiences with internal physical adversity may pre-train organisms and machines to handle external adversity, such as encounters with new environments. Not only has this hypothesis not yet been articulated, mechanisms enabling this phenomenon have yet to be proposed. Here we show a mechanism by which this can occur: we found that physical connectors, in learning to restore behavior to previously independent, morphologically diverse agents they disrupted by tethering them together, trigger and tame sufficiently diverse disruptions that later encounters with new environments trigger disruptions that fall within this manageable range, enabling the collective to continue behaving properly without any additional learning or adaptation. Further, we found that building collectives from more agents, or more diverse agents, further increases the collective's resilience to new environments. This suggests that not just taming but intentionally creating internal physical adversity may indeed prepare organisms for external adversity, and could do so for machines, if they were built from smaller machines.
