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English(EN) What Counts as Strategic Reasoning? A Systematic Mapping of Chess Research on Humans, Engines, and Language Models

国际象棋研究映射突显AI战略推理的差距

一篇新近发表在arXiv上的系统性映射研究,分析了关于战略推理的近期研究,重点关注国际象棋作为模型领域。该研究将研究分为人类棋手、传统国际象棋引擎、神经网络和大型语言模型(LLMs)几类。研究表明,虽然大多数研究集中在态势评估和行动选择上,但显式规划、解释和人机协作等领域仍未得到充分探索。该论文提出了在这些未充分探索领域的未来研究方向,并强调了国际象棋在弥合战略推理的认知和计算视角方面的潜力。 AI

影响 确定了战略推理领域未来AI研究的关键领域,特别是在规划和人机协作方面。

排序理由 该条目是一篇发表在arXiv上的研究论文,详细介绍了对现有研究的系统性映射研究。[lever_c_demoted from research: ic=1 ai=1.0]

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国际象棋研究映射突显AI战略推理的差距

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该条目是一篇发表在arXiv上的研究论文,详细介绍了对现有研究的系统性映射研究。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Paolo Ciancarini, Remo Pareschi ·

    什么是战略性推理?人类、引擎和语言模型国际象棋研究的系统性映射

    arXiv:2609.18286v1 Announce Type: new Abstract: Chess has long served as a model domain for studying search, expertise, decision-making, and artificial intelligence. The emergence of large language models (LLMs) has renewed the relevance of chess as a controlled environment for i…