Title of article :
An overview of reinforcement learning and deep reinforcement learning for conditionbased maintenance
Author/Authors :
Dehghani Ghobadi, Zahra School of Mathematics, Statistics and Computer Science - College of Science - University of Tehran, Tehran, Iran , Haghighi, Firoozeh School of Mathematics, Statistics and Computer Science - College of Science - University of Tehran, Tehran, Iran , Safari, Abdollah School of Mathematics, Statistics and Computer Science - College of Science - University of Tehran, Tehran, Iran
Pages :
9
From page :
81
To page :
89
Abstract :
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.
Keywords :
Condition-based maintenance , Deep reinforcement learning , Markov decision process
Journal title :
International Journal of Reliability, Risk and Safety: Theory and Application
Serial Year :
2021
Record number :
2734646
Link To Document :
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