Keyphrases
Maintenance Scheduling
100%
Effective Maintenance
100%
Multi-component System
100%
Probabilistic Reinforcement Learning
100%
Actor Network
50%
Rule-based
33%
Life Cycle Cost
33%
Policy Optimization
33%
Reinforcement Learning Model
33%
Actor-critic
33%
Convergence Rate
16%
Industrial Application
16%
Local Minima
16%
Sampling Scheme
16%
Environmental Policy
16%
Effective Training
16%
Learning Scheme
16%
Generic Framework
16%
Model Optimization
16%
State Policy
16%
Sampling Efficiency
16%
Uncertainty Quantification
16%
Data Scarcity
16%
Multi-agent Reinforcement Learning
16%
Low Life Cycle Cost
16%
Environmental Modeling
16%
Bayesian Modeling
16%
Reward Model
16%
State Representation
16%
CFM56
16%
Environment Exploration
16%
Guided Sampling
16%
Environmental Reward
16%
Deep Reinforcement Learning (deep RL)
16%
Multi-agent Deep Reinforcement Learning (MADRL)
16%
Critic Network
16%
Engineering
Efficient Maintenance
100%
Multicomponent System
100%
Reinforcement Learning
100%
Lifecycle Cost
33%
Industrial Applications
11%
Shortfall
11%
System Component
11%
Domain Expert
11%
Learning Scheme
11%
Desirable Quality
11%
Convergence Speed
11%
Uncertainty Quantification
11%
Effective Training
11%
Critic Network
11%
Local Minimum
11%
Bayesian Model
11%
Computer Science
Reinforcement Learning
100%
Life Cycle Cost
50%
Optimization Policy
33%
Deep Reinforcement Learning
16%
Local Minimum
16%
Speed Convergence
16%
Multi-Agent Deep Reinforcement Learning
16%
Learning Scheme
16%
Bayesian Model
16%
Sampling Scheme
16%
Multi-Agent Reinforcement Learning
16%
Industrial Applications
16%
Chemical Engineering
Reinforcement Learning
100%