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The large language models represented by ChatGPT have a disruptive impact onthe field of artificial intelligence. But it mainly focuses on natural languageprocessing, speech recognition, machine learning and natural languageunderstanding. This paper innovatively applies the large language model to thefield of intelligent decision-making, places the large language model in thedecision-making center, and constructs an agent architecture with the largelanguage model as the core. Based on this, it further proposes a two-layeragent task planning, issues and executes decision commands through theinteraction of natural language, and carries out simulation verificationthrough the wargame simulation environment. Through the game confrontationsimulation experiment, it is found that the intelligent decision-making abilityof the large language model is significantly stronger than the commonly usedreinforcement learning AI and rule AI, and the intelligence, understandabilityand generalization are all better. And through experiments, it was found thatthe intelligence of the large language model is closely related to prompt. Thiswork also extends the large language model from previous human-computerinteraction to the field of intelligent decision-making, which has importantreference value and significance for the development of intelligentdecision-making.

Self Generated Wargame AI: Double Layer Agent Task Planning Based on Large Language Model