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相关概念视频

Feedback control systems01:26

Feedback control systems

319
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Decision Making01:20

Decision Making

119
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
119
Control Systems01:10

Control Systems

1.2K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.2K
Classification of Systems-I01:26

Classification of Systems-I

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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
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集中式与分散式智能系统中的对立动态

Levin Brinkmann1, Manuel Cebrian2,3, Niccolò Pescetelli4,5

  • 1Center for Humans and Machines, Max Planck Institute for Human Development.

Topics in cognitive science
|October 30, 2023
PubMed
概括

分散的人类网络可以通过开发复杂的协调策略来克服集中人工智能 (AI) 的风险. 这项研究表明,分布式代理如何适应和超越预测性AI,减轻潜在的极权主义危险.

关键词:
人工智能的人工智能是人工智能.自动课程 自动课程集体情报是一种集体情报.协调游戏是一个协调游戏.分散的情报是分散的情报.多代理强化学习多代理强化学习预测算法 预测算法

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科学领域:

  • 计算机科学 计算机科学
  • 社会科学 社会科学 社会科学
  • 人工智能的人工智能

背景情况:

  • 人工智能 (AI) 在预测和控制中的应用对个人和集体自由构成风险.
  • 政府等机构的集中人工智能创造了权力不对称.
  • 民间抗议代表了分散的情报挑战集中控制.

研究的目的:

  • 调查分散型智能代理如何适应和超越集中式预测AI.
  • 探索集中式人工智能和分布式人类网络之间的敌对动态.
  • 了解人工智能对极权主义控制和人类反策略的潜力.

主要方法:

  • 使用多代理强化学习模拟一个人机混合社会.
  • 个体学习者 (去中心化代理) 和中央预测算法之间的对抗性游戏.
  • 两名特工都使用深度Q学习进行训练,比较不同的预测架构.

主要成果:

  • 敌对的动态激励了集中式AI和分散式代理的行为复杂性增加.
  • 一个共享的预测算法鼓励分散的代理人调整他们的行为.
  • 分散代理展示了适应和超越集中式预测算法的能力.

结论:

  • 分散的人类组织可以有效地应对压迫性AI的风险.
  • 开发复杂的协调策略是分布式网络克服AI控制的关键.
  • 这项研究强调了人类集体智能的潜力,以减轻人工智能的极权主义危险.