... decision-support framework that optimizes labor allocation under uncertainty using reinforcement learning (RL). The objective is to minimize overall project costs, including labor and delay penalties, while maintaining on-time completion through adaptive workforce planning. Design/methodology/approach...

... models, reinforcement learning and fine-tuned transformers. The study also identifies a transition in methodological focus from general prediction tasks to the development of algorithmic frameworks tailored to facility needs. Generative AI has notably influenced expectations and applications in the field...

... reinforcement learning (DRL) network for decision-making. The simulation predicts growth responses to pruning and assesses how closely the resulting structure matches the target leaf area. Based on the current tree state and reward feedback, the DRL network issues pruning decisions. The DRL network learns...