A bilevel Proxy-FEA diagnostic framework is introduced and tested on a simplified LDED32 stripe benchmark to reveal proxy misalignment with FEA labels and a stress-distortion trade-off in RL-guided scan-order optimization.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Reinforcement Learning for Laser Additive Manufacturing Scan-Order Optimisation: A Bilevel Proxy--FEA Diagnostic Framework for Reward and World-Model Diagnosis
A bilevel Proxy-FEA diagnostic framework is introduced and tested on a simplified LDED32 stripe benchmark to reveal proxy misalignment with FEA labels and a stress-distortion trade-off in RL-guided scan-order optimization.