Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II

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.

Recommended citation: Weiyu Ma, Dongyu Xu, Shu Lin, Haifeng Zhang, and Jun Wang, "Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II," presented at International Conference on Distributed Artificial Intelligence, Singapore, Singapore, 2024.
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