Alleviating parameter-tuning burden in reinforcement learning for large-scale process control.
Lingwei ZhuGo TakamiMizuo KawaharaHiroaki KanokogiTakamitsu MatsubaraPublished in: Comput. Chem. Eng. (2022)
Keyphrases
- process control
- parameter tuning
- reinforcement learning
- ink bleed
- control system
- intelligent control
- product quality
- small scale
- semiconductor manufacturing
- parameter settings
- pi controller
- function approximation
- state space
- fuzzy logic controller
- multi agent
- machine learning
- real world
- optimal control
- temporal difference
- manufacturing process
- optimal policy
- least squares
- neural network
- software engineering
- genetic algorithm
- graduate education