In this article, we explore neurobiological principles that could be deployed in systems requiring self-preservation, adaptive control, and contextual awareness. We start with low-level control for sensor processing and motor reflexes. We then discuss how critical it is at an intermediate level to maintain homeostasis and predict system set points. We end with a discussion at a high level, or cognitive level, where planning and prediction can further monitor the system and optimize performance. We emphasize the information flow between these levels both from a systems neuroscience and an engineering point of view. Throughout the article, we describe the brain systems that carry out these functions and provide examples from artificial intelligence, machine learning, and robotics which include these features. Our goal is to show how biological organisms performing self-monitoring can inspire the design of autonomous and embedded systems.

中文翻译：

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受神经生物学启发的自我监测系统


在本文中，我们探讨了可以应用于需要自我保护、自适应控制和情境感知的系统中的神经生物学原理。我们从传感器处理和运动反射的低级控制开始。然后我们讨论在中间水平上维持稳态和预测系统设定点的重要性。我们以高层次或认知层次的讨论结束，其中规划和预测可以进一步监控系统并优化性能。我们从系统神经科学和工程学的角度强调这些级别之间的信息流。在整篇文章中，我们描述了执行这些功能的大脑系统，并提供了包含这些功能的人工智能、机器学习和机器人技术的示例。我们的目标是展示生物有机体进行自我监控如何激发自主和嵌入式系统的设计。