Interpretable Input-Output Hidden Markov Model-Based Deep Reinforcement Learning for the Predictive Maintenance of Turbofan Engines

• Published in: Big Data Analytics and Knowledge Discovery pp. 133 - 148
• Main Authors: Abbas, Ammar N., Chasparis, Georgios C., Kelleher, John D.
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Deep Reinforcement Learning (DRL); Input-Output Hidden Markov Model (IOHMM); Interpretable AI; Predictive maintenance

An open research question in deep reinforcement learning is how to focus the policy learning of key decisions within a sparse domain. This paper emphasizes on combining the advantages of input-output hidden Markov models and reinforcement learning. We propose a novel hierarchical modeling methodolog...