Self Generated Wargame AI: Double Layer Agent Task Planning Based on
Large Language Model
- URL: http://arxiv.org/abs/2312.01090v2
- Date: Mon, 18 Dec 2023 07:30:48 GMT
- Title: Self Generated Wargame AI: Double Layer Agent Task Planning Based on
Large Language Model
- Authors: Y.Sun, J.Zhao, C.Yu, W.Wang, X.Zhou
- Abstract summary: This paper innovatively applies the large language model to the field of intelligent decision-making.
It proposes a two-layer agent task planning, issues and executes decision commands through the interaction of natural language.
It is found that the intelligent decision-making ability of the large language model is significantly stronger than the commonly used reinforcement learning AI and rule AI.
- Score: 0.6562256987706128
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The large language models represented by ChatGPT have a disruptive impact on
the field of artificial intelligence. But it mainly focuses on natural language
processing, speech recognition, machine learning and natural language
understanding. This paper innovatively applies the large language model to the
field of intelligent decision-making, places the large language model in the
decision-making center, and constructs an agent architecture with the large
language model as the core. Based on this, it further proposes a two-layer
agent task planning, issues and executes decision commands through the
interaction of natural language, and carries out simulation verification
through the wargame simulation environment. Through the game confrontation
simulation experiment, it is found that the intelligent decision-making ability
of the large language model is significantly stronger than the commonly used
reinforcement learning AI and rule AI, and the intelligence, understandability
and generalization are all better. And through experiments, it was found that
the intelligence of the large language model is closely related to prompt. This
work also extends the large language model from previous human-computer
interaction to the field of intelligent decision-making, which has important
reference value and significance for the development of intelligent
decision-making.
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