基于状态维护的强化学习和深度强化学习概述

Zahra Dehghani Ghobadi, F. Haghighi, Abdollah Safari
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引用次数: 0

摘要

基于状态的维修(CBM)是指根据部件的实际恶化情况做出维修决策。它由一系列表示不同恶化阶段的状态和一组维护动作组成。因此,基于状态的维修是一个顺序决策问题。强化学习(RL)是机器学习的一个子领域,提出用于自动决策。本文概述了迄今为止在基于状态的维护优化中使用的强化学习和深度强化学习方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An overview of reinforcement learning and deep reinforcement learning for condition-based maintenance
Condition-based maintenance (CBM) involves making decisions on maintenance based on the actual deterioration conditions of the components. It consists of a chain of states representing various stages of deterioration and a set of maintenance actions. Therefore, condition-based maintenance is a sequential decision-making problem. Reinforcement Learning(RL) is a subfield of Machine Learning proposed for automated decision-making. This article provides an overview of reinforcement learning and deep reinforcement learning methods that have been used so far in condition-based maintenance optimization
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