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相关概念视频

Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

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Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
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Randomized Experiments01:13

Randomized Experiments

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
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Associative Learning01:27

Associative Learning

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
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Reinforcement01:23

Reinforcement

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Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
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Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.5K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
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Observational Learning01:12

Observational Learning

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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相关实验视频

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在区块链中使用强化学习和在对抗性环境中验证的自适应共识优化.

Rommel Gutierrez1, William Villegas-Ch1, Jaime Govea1

  • 1Escuela de Ingeniería en Ciberseguridad, FICA, Universidad de Las Américas, Quito, Ecuador.

Frontiers in artificial intelligence
|October 16, 2025
PubMed
概括

这项研究介绍了一个自适应的区块链共识架构,使用强化学习来增强安全性和效率. 该系统提高了吞吐量,减少了延迟,并在不利的网络条件下降低了能源消耗.

科学领域:

  • 区块链技术 区块链技术
  • 人工智能的人工智能
  • 网络安全 网络安全

背景情况:

  • 现代区块链网络面临着复杂性和分散性的挑战,在不利的条件下限制了传统的共识协议.
  • 现有系统与实时异常作斗争,如Sybil攻击和网络拥堵,导致性能下降和安全漏洞.
  • 缺乏自主政策调整机制阻碍了适应能力,特别是在资源有限的边缘计算环境中.

研究的目的:

  • 为区块链网络提出适应性共识架构.
  • 增强对抗场景和动态网络条件的弹性.
  • 提高分散系统的效率,安全性和能源消耗.

主要方法:

  • 集成基于图形的近接政策优化 (PPO) 强化学习代理.
  • 在真实流量和合成对抗行为混合数据集上训练代理.
  • 在具有多个威胁载体的压力测试环境中进行评估,包括Sybil攻击和网络拥堵.

主要成果:

  • 在高负载条件下保持稳定的吞吐量 (TPS) 和减少34%的共识延迟.
  • 在Sybil和节点崩场景中实现了高检测率 (DR > 0.90,FPR < 0.10).
  • 在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在稳定的收和适应的情况下,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵和易发生事故的场景中,在高拥堵的场景中.
关键词:
适应性共识机制的共识机制.人工智能的人工智能是人工智能.能源效率边缘验证验证恶意节点检测 恶意节点检测在区块链中进行强化学习.

相关实验视频

Last Updated: May 5, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Published on: September 8, 2023

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结论:

  • 拟议的自适应共识架构有效地提高了区块链性能和安全性.
  • 强化学习的整合提供了强大的适应动态和对抗性的网络条件.
  • 该系统显示了在边缘计算和超越现实世界的部署的巨大潜力.