Investigating the use of reinforcement learning for multi-fidelity model selection in the context of design decision making

Mathematics

• Reinforcement Learning 100%
• Fidelity 83%
• Decision Making 66%
• Model Selection 66%
• Design 41%
• Context 41%
• Model 21%
• Design Process 21%
• Policy 21%
• Modeling 19%
• Sequencing 17%
• Q-learning 12%
• Model Evaluation 11%
• Methodology 10%
• Markov Decision Process 9%
• Computational Model 8%
• Unknown 4%
• Converge 4%
• Framework 4%

Engineering & Materials Science

• Reinforcement learning 66%
• Decision making 48%
• Design aids 7%
• Markov processes 5%
• Costs 4%
• Engineers 3%