Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II
August 05, 2025 Β· Declared Dead Β· π Proceedings of the 2024 Sixth International Conference on Distributed Artificial Intelligences
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Authors
Weiyu Ma, Dongyu Xu, Shu Lin, Haifeng Zhang, Jun Wang
arXiv ID
2508.16580
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
1
Venue
Proceedings of the 2024 Sixth International Conference on Distributed Artificial Intelligences
Last Checked
4 months ago
Abstract
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.
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