ALPHA adaptively selects among non-hierarchical low-fidelity models during reinforcement learning, using policy alignment with the high-fidelity policy to train a high-quality design policy.
A Review of Surrogate Modeling Techniques for Aerodynamic Analysis and Optimization: Current Limitations and Future Challenges in Industry,
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Adaptive Learning of Design Strategies over Non-Hierarchical Multi-Fidelity Models via Policy Alignment
ALPHA adaptively selects among non-hierarchical low-fidelity models during reinforcement learning, using policy alignment with the high-fidelity policy to train a high-quality design policy.