Reinforcement Learning in Flashlight and Arrayfire

This study explores reinforcement learning (RL) as a data-driven approach to optimize hand choice in sequential assembly operations. Using structured left-and right-hand process charts from flashlight assembly tasks, RL agents were trained on annotated datasets to redistribute actions across both hands.