LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models
On the map: LLM reasoning → Reasoning for agents, planning and code
Abstract (arXiv)
This paper presents a comprehensive survey of the current status and opportunities for Large Language Models (LLMs) in strategic reasoning, a sophisticated form of reasoning that necessitates understanding and predicting adversary actions in multi-agent settings while adjusting strategies accordingly. Strategic reasoning is distinguished by its focus on the dynamic and uncertain nature of interactions among multi-agents, where comprehending the environment and anticipating the behavior of others is crucial. We explore the scopes, applications, methodologies, and evaluation metrics related to strategic reasoning with LLMs, highlighting the burgeoning development in this area and the interdisciplinary approaches enhancing their decision-making performance. It aims to systematize and clarify the scattered literature on this subject, providing a systematic review that underscores the importance of strategic reasoning as a critical cognitive capability and offers insights into future research directions and potential improvements.
Key facts. Cited by 97 papers in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 71 of its 92 references that are in the map. First posted on arXiv 1 Apr 2024.
Builds on
71 of 92 references.
Closest ancestors · 9
Same direction, newest first
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Other references · 62
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Citing papers per year: 2024: 25; 2025: 51; 2026: 21.
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