From Natural Language to Simulations: Applying GPT-3 Codex to Automate Simulation Modeling of Logistics Systems
Our work is the first attempt to apply Natural Language Processing to automate the development of simulation models of logistics systems. We demonstrated that the framework built on top of the fine-tuned Transdormer-based language model could produce functionally valid simulations of queuing and inventory control systems given the verbal description. The proposed framework has the potential to remove the tedium of programming and allow experts to focus on the high-level consideration of the problem and holistic thinking.
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