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相关概念视频

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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相关实验视频

Updated: May 20, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
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在AlphaZero中通过概念发现和转移弥合人类-AI知识差距.

Lisa Schut1, Nenad Tomašev2, Thomas McGrath3

  • 1Oxford Applied and Theoretical Machine Learning Group, Department of Computer Science, University of Oxford, Oxford OX1 3QG, United Kingdom.

Proceedings of the National Academy of Sciences of the United States of America
|March 26, 2025
PubMed
概括

研究人员开发了一种方法,从AI系统AlphaZero中提取新的国际象棋概念. 这些概念提高了大师的表现,展示了AI.

关键词:
在这里,我们可以看到AIAIAI.概念发现 概念发现机器学习是机器学习.强化学习是一种强化学习.

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科学领域:

  • 人工智能的人工智能
  • 认知科学 认知科学
  • 游戏理论 游戏理论

背景情况:

  • 人工智能 (AI) 系统在各种领域表现出超人类的性能.
  • 从人工智能中提取内部知识是具有挑战性的,因为它具有庞大的表示空间.
  • 利用人工智能知识可以显著提高人类的理解和能力.

研究的目的:

  • 开发一种方法来从AI中提取新的和可教的概念.
  • 验证提取的AI概念在推进人类知识中的实用性.
  • 展示AI作为新概念发现的来源的潜力.

主要方法:

  • 从AlphaZero的内部表示中挖掘概念向量,使用凸式优化.
  • 根据可教性和新性标准对提取的概念进行过.
  • 通过使用国际象棋拼图解决方案原型的专家评估验证概念.

主要成果:

  • 一种新的方法成功地从AlphaZero中提取了有意义的象棋概念.
  • 提取的概念可以转移到另一个AI代理,并包含新的信息.
  • 国际象棋大师在学习AI衍生概念后,表现有所改善.
  • 发现这些概念处于当前人类国际象棋理解的前沿.

结论:

  • 人工智能系统可以成为发现超越人类专业知识的新知识的来源.
  • 开发的方法为利用AI知识提取提供了概念验证.
  • 这种方法对推进人类知识和跨应用程序的人类-人工智能交互具有深远的影响.