mlsanityData to 14 Oct 2026

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

arXiv 2508.16580 ↗First posted 5 Aug 2025cs.HC cs.AIcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 37 references that are in the map. First posted on arXiv 5 Aug 2025.

Builds on

15 of 37 references.

References · 15

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  4. 2023Qwen Technical Reportcited by 3,344
  5. 2020ALFWorld: Aligning Text and Embodied Environments for Interactive Learningcited by 1,205
  6. 2023Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memorycited by 289
  7. 2017StarCraft II: A New Challenge for Reinforcement Learningcited by 274
  8. 2017Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Gamescited by 96
  9. 2023Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approachcited by 79
  10. 2024Large Language Model-based Human-Agent Collaboration for Complex Task Solvingcited by 38
  11. 2024Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolfcited by 24
  12. 2022On Efficient Reinforcement Learning for Full-length Game of StarCraft IIcited by 14
3 more
  1. 2019Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learningcited by 11
  2. 2021An Introduction of mini-AlphaStarcited by 10
  3. 2019Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learningcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025The Landscape of Agentic Reinforcement Learning for LLMs: A Surveycited by 205
  2. 2025Shall We Play a Game? Language Models for Open-ended Wargamescited by 2
  3. 2026Decoupled Travel Planning with Behavior Forestcited by 1