3 papers
cs.HC2025
Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II
Weiyu Ma, Dongyu Xu, Shu Lin +2
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 focu…
cs.AI2025
TacticCraft: Natural Language-Driven Tactical Adaptation for StarCraft II
Weiyu Ma, Jiwen Jiang, Haobo Fu +1
We present an adapter-based approach for tactical conditioning of StarCraft II AI agents. Current agents, while powerful, lack the ability to adapt their strategies based on high-l…
cs.AI2025
SMAC-R1: The Emergence of Intelligence in Decision-Making Tasks
Yue Deng, Weiyu Ma, Yuxin Fan +4
StarCraft Multi-Agent Challenge (SMAC) has been one of the most commonly used experimental environments in multi-agent reinforcement learning (MARL), where the specific task is to…