arXiv AI August 12, 2026 By Khanh Quan Pham, Majid Kundroo, Geunwoo Ban, Seongho Bae, Taehong Kim

Reinforcement Learning-Based Laser Cutting Machine Parameter Optimization

arXiv:2608. 10549v1 Announce Type: new Abstract: Achieving high accuracy in laser-based cutting of optical films requires careful tuning of parameters such as focal length and laser power beam, adjusted according to the specific properties of each film type.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

reinforcement-learning

arXiv AI

Jun 19

Multi-Head Attention-Based Feature Extractor Integration with Soft Actor-Critic for Porosity Prediction and Process Parameter Optimization in Additive Manufacturing

arXiv:2606. 20087v1 Announce Type: new Abstract: Additive manufacturing process optimization requires precise parameter control to minimize defects such as porosity.

By Kianoush Aqabakee, Leonardo Stella

agents reinforcement-learning

arXiv Machine Learning

Jun 30

Reinforcement Learning with a Bilevel World-Model Architecture for Scan-Order Optimisation in Laser Directed Energy Deposition

arXiv:2605. 25063v2 Announce Type: replace Abstract: Scan-order design in laser directed energy deposition (LDED) is a delayed, path-dependent thermo-mechanical decision problem, because sequence quality becomes observable only after the complete deposition and cooling cycle.

By Xian Wu, Haoran Li, Yuanqi Chu, Dongbin Zhao, Bin Wang

reinforcement-learning safety

arXiv AI

2d ago

Reinforcement Learning-Based Production Scheduling in an Industry-Based Coating Scenario Using the Digital Model Playground

arXiv:2608. 14122v1 Announce Type: new Abstract: Production scheduling in complex manufacturing environments is challenging when sequence-dependent setup times, stochastic disturbances, and due-date constraints must be addressed simultaneously.

By Arne Kr\"oger, Ralf Buscherm\"ohle, Wilhelm Hasselbring, Henrik Wilbers

agents reinforcement-learning benchmarks

arXiv AI

Jun 10

Event-Driven Reinforcement Learning Enables Long-Horizon Control in Semiconductor Fabrication

arXiv:2606. 10705v1 Announce Type: cross Abstract: Reinforcement learning promises to optimize sequential decisions in large-scale systems.

By Yavar Yeganeh, Mahsa Shekari, Nicla Frigerio, Daniele Pagano, Andrea Matta

agents reinforcement-learning efficiency

arXiv AI

Jun 17

When Life Gives You BC, Make Q-functions: Extracting Q-values from Behavior Cloning for On-Robot Reinforcement Learning

arXiv:2605. 05172v2 Announce Type: replace-cross Abstract: Behavior Cloning (BC) has emerged as a highly effective paradigm for robot learning.

By Lakshita Dodeja, Ondrej Biza, Shivam Vats, Stephen Hart, Stefanie Tellex, Robin Walters, Karl Schmeckpeper, Thomas Weng

reinforcement-learning robotics benchmarks

arXiv AI

Jul 28

When Every Simulation Counts: Value-Based Reinforcement Learning for Accelerated Photonics Inverse Design

arXiv:2607. 23469v1 Announce Type: cross Abstract: Photonic-crystal surface-emitting lasers (PCSELs) can combine high-power operation with narrow-divergence surface emission, but optimizing coupled parameters requires costly full-wave simulations.

By Longying Wen, Feiyang Wu, Jinglin Yu, Chongxian Yuan, Renjie Li, Zhaoyu Zhang

reinforcement-learning

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Multi-Head Attention-Based Feature Extractor Integration with Soft Actor-Critic for Porosity Prediction and Process Parameter Optimization in Additive Manufacturing

Reinforcement Learning with a Bilevel World-Model Architecture for Scan-Order Optimisation in Laser Directed Energy Deposition

Reinforcement Learning-Based Production Scheduling in an Industry-Based Coating Scenario Using the Digital Model Playground

Event-Driven Reinforcement Learning Enables Long-Horizon Control in Semiconductor Fabrication

When Life Gives You BC, Make Q-functions: Extracting Q-values from Behavior Cloning for On-Robot Reinforcement Learning

When Every Simulation Counts: Value-Based Reinforcement Learning for Accelerated Photonics Inverse Design