Health state prediction with reinforcement learning for predictive maintenance
The findings highlight the potential of RL for predictive maintenance applications and underscore the importance of aligning algorithm design with environment characteristics and reward structures.
Authors
- Gregoris Mentzas (ORCID: https://orcid.org/0000-0002-3305-3796)
- Stefanos Kontos
- Anastasis Aglogallos
- Alexandros Bousdekis
Institutions
- National Technical University of Athens (GR)
- Institute of Communication and Computer Systems (GR)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2026-01-12
- DOI
- https://doi.org/10.3389/frai.2025.1720140
- Primary Topic
- Machine Fault Diagnosis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- HORIZON EUROPE Framework Programme