Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Randomized Experiments01:13

Randomized Experiments

7.0K
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...
7.0K
Random Variables01:09

Random Variables

12.3K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
12.3K
Variance01:15

Variance

9.8K
 The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.
The standard deviation measures the spread in the same units as the...
9.8K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

703
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
703
Random Sampling Method01:09

Random Sampling Method

11.2K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.2K
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

575
Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
575

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

CARS_SPA optimized UV-Vis spectroscopy for rapid and robust COD prediction in water samples.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2026
Same author

Licochalcone a Disrupted Mitochondrial Function to Promote Cuproptosis in Glioblastoma Through Regulating RAS/MAPK Pathway.

Applied biochemistry and biotechnology·2026
Same author

Bidirectional effect modification between diurnal temperature range and particulate matter on acute myocardial infarction risk.

iScience·2026
Same author

6H2L, a novel derivative of bifendate, dually suppresses glycolysis and glutaminolysis in hepatocellular carcinoma via inhibiting YAP stability.

Chemico-biological interactions·2026
Same author

The effect of web-based learning with peer-facilitated discussion on nursing students' knowledge and practices in work-related biological exposure: a quasi-experimental study.

BMC medical education·2026
Same author

Sodiophilic Hosts With Pseudocapacitive Kinetics for Robust Anode-Free Sodium Metal Batteries.

Angewandte Chemie (International ed. in English)·2026

相关实验视频

Updated: Jul 11, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.0K

偏差减少域随机化用于强化学习与政策梯度的强化学习.

Yuankun Jiang, Chenglin Li, Wenrui Dai

    IEEE transactions on pattern analysis and machine intelligence
    |November 6, 2023
    PubMed
    概括

    域随机化 (DR) 增强了深度强化学习的概括性,但增加了训练差异. 本研究引入了一种减少差异域随机化 (VRDR) 方法,具有最佳基线,以提高机器人控制任务中的样本效率和政策性能.

    科学领域:

    • 机器人技术 机器人技术 机器人技术
    • 机器学习 机器学习
    • 人工智能的人工智能

    背景情况:

    • 域随机化 (DR) 对于通过引入环境多样性来提高深度强化学习 (DRL) 政策的泛化能力至关重要.
    • 然而,由于环境变化的增加,DR加剧了政策梯度变化,阻碍了DRL培训中的样本效率.
    • 在DR中,标准基线往往无法充分缓解这种高差异,导致训练表现低于最佳.

    研究的目的:

    • 从理论上推导出DRL中域随机化 (DR) 的无偏差,状态/环境依赖的最佳基线.
    • 提出一种新的减差域随机化 (VRDR) 方法,以平衡减差与计算可行性.
    • 证明VRDR在加速融合和提高机器人控制政策稳定性和绩效方面的有效性.

    主要方法:

    • 对DR的最佳基线的理论推导,该基线可以考虑状态和环境的依赖性.
    • 开发了减少差异域随机化 (VRDR) 方法,该方法估计了环境子空间内的基线.
    • 在6个具有随机动态的机器人控制任务上对VRDR的实证评估.

    主要成果:

    • 建议的最佳基线理论上保证了与标准常数和状态依赖基线相比,在DR中进一步减少差异.
    • 与国家依赖的基线相比,VRDR显示了政策培训趋同的显著加速.

    更多相关视频

    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice
    08:59

    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice

    Published on: March 3, 2023

    2.1K
    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    596

    相关实验视频

    Last Updated: Jul 11, 2025

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice
    08:59

    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice

    Published on: March 3, 2023

    2.1K
    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    596
  • 经验结果表明VRDR始终实现优越的最终政策,在多个机器人任务中提高了训练稳定性.
  • 结论:

    • 新的VRDR方法有效地减少了对DR的政策梯度估计的差异.
    • 在随机环境中,VRDR提供了一种实用且有理论依据的方法,以提高DRL培训效率和最终政策质量.
    • 这项工作为将DRL应用于需要强有力的概括的现实世界机器人系统提供了重大进展.