Matches in SemOpenAlex for { <https://semopenalex.org/work/W4377018097> ?p ?o ?g. }
- W4377018097 endingPage "103487" @default.
- W4377018097 startingPage "103487" @default.
- W4377018097 abstract "Nowadays, modern engineering systems require sophisticated maintenance strategies to ensure their correct performance. Maintenance has become one of the most important tasks of the systems lifecycle. This paper presents a literature review of the application of Reinforcement Learning algorithms for the maintenance of engineering systems. Reinforcement Learning-based maintenance has been classified regarding four types of system: transportation systems, manufacturing and production systems, civil infrastructures, power and energy systems, and other systems. Based on the literature review, this paper includes an overall analysis of the current state and a discussion of main limitations, challenges, and future trends in this field. A summary table is provided to present clearly the most important references. This research work demonstrates that Reinforcement Learning algorithms have a great potential for generating maintenance policies, outperforming most conventional strategies." @default.
- W4377018097 created "2023-05-19" @default.
- W4377018097 creator A5027211124 @default.
- W4377018097 date "2023-09-01" @default.
- W4377018097 modified "2023-10-02" @default.
- W4377018097 title "Applications of Reinforcement Learning for maintenance of engineering systems: A review" @default.
- W4377018097 cites W1914583973 @default.
- W4377018097 cites W1977655452 @default.
- W4377018097 cites W2017364480 @default.
- W4377018097 cites W2026536622 @default.
- W4377018097 cites W2046376809 @default.
- W4377018097 cites W2062525454 @default.
- W4377018097 cites W206679605 @default.
- W4377018097 cites W2090076230 @default.
- W4377018097 cites W2090089645 @default.
- W4377018097 cites W2099618002 @default.
- W4377018097 cites W2107726111 @default.
- W4377018097 cites W2112794044 @default.
- W4377018097 cites W2119717200 @default.
- W4377018097 cites W2127558639 @default.
- W4377018097 cites W2131065845 @default.
- W4377018097 cites W2159185621 @default.
- W4377018097 cites W2160362462 @default.
- W4377018097 cites W2430768047 @default.
- W4377018097 cites W2580909119 @default.
- W4377018097 cites W2768919152 @default.
- W4377018097 cites W2768978102 @default.
- W4377018097 cites W2894984701 @default.
- W4377018097 cites W2898035736 @default.
- W4377018097 cites W2898897140 @default.
- W4377018097 cites W2920054549 @default.
- W4377018097 cites W2921732122 @default.
- W4377018097 cites W2944766483 @default.
- W4377018097 cites W2952242647 @default.
- W4377018097 cites W2965512832 @default.
- W4377018097 cites W2981038142 @default.
- W4377018097 cites W2985465748 @default.
- W4377018097 cites W2990681646 @default.
- W4377018097 cites W2996738572 @default.
- W4377018097 cites W3005832962 @default.
- W4377018097 cites W3015872947 @default.
- W4377018097 cites W3016686916 @default.
- W4377018097 cites W3026899377 @default.
- W4377018097 cites W3033271224 @default.
- W4377018097 cites W3037319445 @default.
- W4377018097 cites W3037851088 @default.
- W4377018097 cites W3040266569 @default.
- W4377018097 cites W3043388922 @default.
- W4377018097 cites W3082233933 @default.
- W4377018097 cites W3091780726 @default.
- W4377018097 cites W3095190713 @default.
- W4377018097 cites W3099862385 @default.
- W4377018097 cites W3100789280 @default.
- W4377018097 cites W3110971738 @default.
- W4377018097 cites W3111381631 @default.
- W4377018097 cites W3112348498 @default.
- W4377018097 cites W3120771501 @default.
- W4377018097 cites W3123082711 @default.
- W4377018097 cites W3132039172 @default.
- W4377018097 cites W3134861104 @default.
- W4377018097 cites W3138984732 @default.
- W4377018097 cites W3155179702 @default.
- W4377018097 cites W3155444895 @default.
- W4377018097 cites W3158411095 @default.
- W4377018097 cites W3170112077 @default.
- W4377018097 cites W3171908814 @default.
- W4377018097 cites W3185338902 @default.
- W4377018097 cites W3195397774 @default.
- W4377018097 cites W3199652046 @default.
- W4377018097 cites W3204619899 @default.
- W4377018097 cites W3211489071 @default.
- W4377018097 cites W3215697635 @default.
- W4377018097 cites W32403112 @default.
- W4377018097 cites W4200162182 @default.
- W4377018097 doi "https://doi.org/10.1016/j.advengsoft.2023.103487" @default.
- W4377018097 hasPublicationYear "2023" @default.
- W4377018097 type Work @default.
- W4377018097 citedByCount "3" @default.
- W4377018097 countsByYear W43770180972023 @default.
- W4377018097 crossrefType "journal-article" @default.
- W4377018097 hasAuthorship W4377018097A5027211124 @default.
- W4377018097 hasConcept C112930515 @default.
- W4377018097 hasConcept C127413603 @default.
- W4377018097 hasConcept C154945302 @default.
- W4377018097 hasConcept C201995342 @default.
- W4377018097 hasConcept C202444582 @default.
- W4377018097 hasConcept C33923547 @default.
- W4377018097 hasConcept C41008148 @default.
- W4377018097 hasConcept C71924100 @default.
- W4377018097 hasConcept C9652623 @default.
- W4377018097 hasConcept C97541855 @default.
- W4377018097 hasConceptScore W4377018097C112930515 @default.
- W4377018097 hasConceptScore W4377018097C127413603 @default.
- W4377018097 hasConceptScore W4377018097C154945302 @default.
- W4377018097 hasConceptScore W4377018097C201995342 @default.
- W4377018097 hasConceptScore W4377018097C202444582 @default.
- W4377018097 hasConceptScore W4377018097C33923547 @default.
- W4377018097 hasConceptScore W4377018097C41008148 @default.