arXiv:2606.20231cs.AIcond-mat.stat-mech2026-06

用热力学定义智能:放大罕见但合法的未来可能性。

Thermodynamic Measure of Intelligence

论文配图:Thermodynamic Measure of Intelligence
图 1 · 摘自论文原文
  • 通过递归自模拟,系统识别并放大罕见但合法的未来
  • 高稀有有效提升需高保真度自模拟,且需有效策略
  • 适用于从物理系统到大模型的通用智能衡量

能否衡量智能?我们提出,智能可定义为对罕见但合法未来的合法放大:系统提高在被动演化下不可能发生、但在领域约束下仍可接受的结果的概率。智能系统必须建模世界及其自身位置。由于系统是其所建模世界的一部分,自然引出递归自模拟:系统在未来的表示中包含自身行动。核心结果表明,在给定假设下,该架构与精确的热力学度量——稀有有效未来的合法放大——存在必要性与近似充分性关系:除非内部模拟以高保真度识别稀有有效未来,否则无法实现高稀有有效提升;反之,当稀有有效保真度高且模拟包含有效策略时,可达提升接近作用力极限最优值。因此,递归自模拟不仅是智能的合理特征,更是高热力学智能所必需且近乎充分的条件。该框架使智能可在全尺度上测量,涵盖从被动物质、反馈控制器、大语言模型到类麦克斯韦妖信息引擎。

原文摘要 · Abstract (English)

Can intelligence be measured? We propose that intelligence can be defined as the lawful amplification of rare but valid futures: a system increases the probability of outcomes that would be unlikely under passive dynamics but remain admissible under the constraints of the domain. We start with the premise that an intelligent system must model the world and its own place within it. Because the system is part of the world it models, this leads naturally to recursive self-simulation: the system represents futures in which its own actions are part of the trajectory. Our central results give a necessity statement and a conditional near-sufficiency statement connecting this architecture to a precise thermodynamic measure of lawful amplification of rare-valid futures: high rare-valid lift is impossible unless the internal simulation identifies rare-valid futures with high fidelity; conversely, when rare-valid fidelity is high and the simulation contains an effective policy, the achievable lift approaches the actuation-limited optimum. Thus recursive self-simulation is not merely a plausible feature of intelligence but, under the stated assumptions, is necessary and nearly sufficient for high thermodynamic intelligence. The resulting framework makes intelligence measurable on a universal scale, from passive matter and feedback controllers, large language models, and humans as text generators to Maxwell-demon-like information engines.

智能测量热力学自模拟稀有未来

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