Jove
Visualize
联系我们

相关概念视频

Observational Learning01:12

Observational Learning

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 because...
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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...
Hindsight Biases01:12

Hindsight Biases

Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
Associative Learning01:27

Associative Learning

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...
Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.

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

K-Alpha Calculator-Krippendorff's Alpha Calculator: A user-friendly tool for computing Krippendorff's Alpha inter-rater reliability coefficient.

MethodsX·2024
Same author

Testing the convergent validity, domain generality, and temporal stability of selected measures of people's tendency to explore.

Nature communications·2024
Same author

LDA2Net Digging under the surface of COVID-19 scientific literature topics via a network-based approach.

PloS one·2024
Same author

The architecture of partisan debates: The online controversy on the no-deal Brexit.

PloS one·2022
Same author

Representation of Jews and Anti-Jewish Bias in 19th Century French Public Discourse: Distant and Close Reading.

Frontiers in big data·2022
Same author

Percent framing attenuates the magnitude effect in a preference-matching task of intertemporal choice.

PloS one·2022
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

相关实验视频

Updated: Jul 7, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

通过遗憾驱动的神经网络预测人类互动学习.

Davide Marchiori1, Massimo Warglien

  • 1Interdepartmental Center for Research Training in Economics and Management (CIFREM), University of Trento, Italy.

Science (New York, N.Y.)
|February 23, 2008
PubMed
概括

在游戏中模拟人类互动学习的神经网络准确预测行为. 基于遗憾的反显著提高了预测,在理解社会学习动态方面表现优于传统经济模型.

科学领域:

  • 认知科学 认知科学
  • 神经科学是一个神经科学.
  • 游戏理论 游戏理论

背景情况:

  • 人类在社会环境中的学习本质上是互动的,个人学习受到其他人的并发学习的影响.
  • 游戏是交互式决策场景的标准模型.
  • 了解和预测交互式学习在社会环境中至关重要.

研究的目的:

  • 探索神经网络在模拟和预测在重复游戏环境中的人类互动学习中的有效性.
  • 评估基于遗憾的反对这些模型的预测准确性的影响.
  • 为了比较基于遗憾的神经网络模型与既有经济模型的性能.

主要方法:

  • 利用设计用于模拟学习过程的简单神经网络.
  • 将基于遗憾的反机制纳入学习网络.
  • 在21个不同的游戏中测试了这些模型,其中包括独特的混合策略平衡.
  • 与实验环境中观察到的人类行为的模型预测进行了比较.

主要成果:

  • 即使是基础的神经网络与基于遗憾的反也准确地预测了重复游戏中的人类行为.
  • 将遗憾纳入反机制大大提高了神经网络的预测性能.
  • 与传统经济模型相比,基于遗憾的模型表现出优越的预测能力.

相关实验视频

Last Updated: Jul 7, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

结论:

  • 神经网络,特别是在结合基于遗憾的反时,为模拟人类交互式学习提供了强大的工具.
  • 遗憾是社会学习的一个关键因素,可以通过计算模型有效地捕捉到.
  • 这些发现表明,通过计算方法推进我们对交互式决策和社会学习的理解有希望的方向.