Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912784354115584 |
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| author | Ma, Weiyu Xu, Dongyu Lin, Shu Zhang, Haifeng Wang, Jun |
| author_facet | Ma, Weiyu Xu, Dongyu Lin, Shu Zhang, Haifeng Wang, Jun |
| contents | We present Adaptive Command, a novel framework integrating large language models (LLMs) with behavior trees for real-time strategic decision-making in StarCraft II. Our system focuses on enhancing human-AI collaboration in complex, dynamic environments through natural language interactions. The framework comprises: (1) an LLM-based strategic advisor, (2) a behavior tree for action execution, and (3) a natural language interface with speech capabilities. User studies demonstrate significant improvements in player decision-making and strategic adaptability, particularly benefiting novice players and those with disabilities. This work contributes to the field of real-time human-AI collaborative decision-making, offering insights applicable beyond RTS games to various complex decision-making scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_16580 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II Ma, Weiyu Xu, Dongyu Lin, Shu Zhang, Haifeng Wang, Jun Human-Computer Interaction Artificial Intelligence We present Adaptive Command, a novel framework integrating large language models (LLMs) with behavior trees for real-time strategic decision-making in StarCraft II. Our system focuses on enhancing human-AI collaboration in complex, dynamic environments through natural language interactions. The framework comprises: (1) an LLM-based strategic advisor, (2) a behavior tree for action execution, and (3) a natural language interface with speech capabilities. User studies demonstrate significant improvements in player decision-making and strategic adaptability, particularly benefiting novice players and those with disabilities. This work contributes to the field of real-time human-AI collaborative decision-making, offering insights applicable beyond RTS games to various complex decision-making scenarios. |
| title | Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2508.16580 |