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

Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

1.7K
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...
1.7K
Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

323
Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
323
Reinforcement01:23

Reinforcement

202
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:
202
Observational Learning01:12

Observational Learning

168
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...
168
Reinforcement Schedules01:24

Reinforcement Schedules

144
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
144
Associative Learning01:27

Associative Learning

345
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...
345

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

A circular "capture-and-upcycle" strategy for micro/nano-plastic remediation: From aquatic pollutants to fire-safe composites.

Journal of hazardous materials·2026
Same author

Nanoplatform-Based Delivery Systems for PROTACs.

Drug development research·2026
Same author

BETAV: A Unified BEV-Transformer and Bézier Optimization Framework for Jointly Optimized End-to-End Autonomous Driving.

Sensors (Basel, Switzerland)·2025
Same author

Hybrid Supervised and Reinforcement Learning for Motion-Sickness-Aware Path Tracking in Autonomous Vehicles.

Sensors (Basel, Switzerland)·2025
Same author

A Novel Integrated Path Planning and Mode Decision Algorithm for Wheel-Leg Vehicles in Unstructured Environment.

Sensors (Basel, Switzerland)·2025
Same author

Nanomedicines Targeting Metabolic Pathways in the Tumor Microenvironment: Future Perspectives and the Role of AI.

Metabolites·2025

相关实验视频

Updated: Jun 27, 2025

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
11:32

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning

Published on: January 19, 2022

3.4K

基于安全深度增强学习的自适应式巡航控制.

Rui Zhao1, Kui Wang2, Wenbo Che1

  • 1College of Automotive Engineering, Jilin University, Changchun 130025, China.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
概括

本研究介绍了安全优先强化学习自适应巡航控制 (SFRL-ACC),这是一种使用深度强化学习进行高效和安全驾驶的新型系统. 在计算时间,交通效率,驾驶舒适性和安全性方面,SFRL-ACC的性能优于传统方法.

关键词:
适应式巡航控制器 适应式巡航控制器自动驾驶自动驾驶的自动驾驶.深度强化学习的学习.预计受约束的政策优化政策优化意识到安全,意识到安全.

更多相关视频

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
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

136

相关实验视频

Last Updated: Jun 27, 2025

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
11:32

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning

Published on: January 19, 2022

3.4K
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
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

136

科学领域:

  • 汽车工程 汽车工程
  • 人工智能的人工智能
  • 控制系统 控制系统

背景情况:

  • 目前的自适应巡航控制 (ACC) 方法面临着模拟困难和计算效率的挑战.
  • 基于优化控制的ACC系统往往难以平衡性能与安全性和舒适性.

研究的目的:

  • 提出一个新的自适应巡航控制系统,安全第一强化学习自适应巡航控制 (SFRL-ACC),利用深度强化学习 (DRL).
  • 通过提高计算效率,安全性和驾驶舒适性来克服现有的ACC方法的局限性.

主要方法:

  • 使用受约束的马尔科夫决策过程 (CMDP) 制定了ACC问题作为安全的DRL问题.
  • 开发了基于预测受约束政策优化 (PCPO) 的 ACC 算法 (SFRL-ACC) 来解决CMDP.
  • 将安全约束纳入DRL政策更新中,使用Kullback-Leibler (KL) 差异信任区域.

主要成果:

  • 与基于最先进的模型预测控制 (MPC) 的ACC方法相比,SFRL-ACC系统表现出更高的性能.
  • 实验结果显示,计算时间,交通效率,驾驶舒适度和安全性都有所改善.
  • 在遵守安全成本限制的同时,PCPO算法有效地最大限度地提高了性能.

结论:

  • SFRL-ACC为当前的ACC系统提供了一个更高效,更安全,更舒适的替代方案.
  • 提出的安全DRL方法有效地解决了ACC控制的复杂性.
  • 这项研究强调了DLR在开发先进汽车控制系统方面的潜力.