复杂网络中的衰老最优控制。
Optimal control of aging in complex networks.
机构信息
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138.
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138;
出版信息
Proc Natl Acad Sci U S A. 2020 Aug 25;117(34):20404-20410. doi: 10.1073/pnas.2006375117. Epub 2020 Aug 12.
Many complex systems experience damage accumulation, which leads to aging, manifest as an increasing probability of system collapse with time. This naturally raises the question of how to maximize health and longevity in an aging system at minimal cost of maintenance and intervention. Here, we pose this question in the context of a simple interdependent network model of aging in complex systems and show that it exhibits cascading failures. We then use both optimal control theory and reinforcement learning alongside a combination of analysis and simulation to determine optimal maintenance protocols. These protocols may motivate the rational design of strategies for promoting longevity in aging complex systems with potential applications in therapeutic schedules and engineered system maintenance.
许多复杂系统都会经历损伤积累，从而导致老化，表现为系统崩溃的概率随着时间的推移而增加。这自然而然地提出了一个问题，即在最小的维护和干预成本下，如何使老化系统的健康和寿命最大化。在这里，我们在复杂系统老化的简单相依网络模型的背景下提出了这个问题，并表明它表现出级联故障。然后，我们使用最优控制理论和强化学习，以及分析和模拟的结合，来确定最优的维护方案。这些方案可能会激励人们设计策略，以促进老化的复杂系统的长寿，这在治疗方案和工程系统维护方面具有潜在的应用。
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