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

Machines: Problem Solving II01:30

Machines: Problem Solving II

310
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
310
Reinforcement01:23

Reinforcement

212
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:
212
Machines: Problem Solving I01:22

Machines: Problem Solving I

327
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
327
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.1K
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...
3.1K
Social Loafing01:37

Social Loafing

34.8K
Another way in which a group presence can affect performance is social loafing—the exertion of less effort by a person working together with a group. Social loafing occurs when our individual performance cannot be evaluated separately from the group. Thus, group performance declines on easy tasks (Karau & Williams, 1993). Essentially individual group members loaf and let other group members pick up the slack. Because each individual’s efforts cannot be evaluated,...
34.8K

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

BaleUAVision: Hay Bales UAV Captured Dataset.

Scientific data·2026
Same author

Agentic LLM-based robotic systems for real-world applications: a review on their agenticness and ethics.

Frontiers in robotics and AI·2025
Same author

Delivering data: A real-world dataset for last-mile delivery optimization.

Data in brief·2025
Same author

Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis.

Journal of functional morphology and kinesiology·2025
Same author

On complexity of colloid cellular automata.

Scientific reports·2024
Same author

A Biologically Inspired Movement Recognition System with Spiking Neural Networks for Ambient Assisted Living Applications.

Biomimetics (Basel, Switzerland)·2024
Same journal

Passive wheels on legged robots: a survey.

Frontiers in robotics and AI·2026
Same journal

Politeness cannot make up for robots' errors.

Frontiers in robotics and AI·2026
Same journal

Workers expect basic social skills but limited autonomy from future robots - a qualitative interview study and taxonomy for robot social skills.

Frontiers in robotics and AI·2026
Same journal

Human-robot interaction in sustainable hospitality: how robot type shapes customer emotions, green perceptions, and service loyalty.

Frontiers in robotics and AI·2026
Same journal

Dynamic variance-aware federated tuning for efficient autonomous vehicle perception under non-IID settings.

Frontiers in robotics and AI·2026
Same journal

Editorial: Synergizing large language models and computational intelligence for advanced robotic systems.

Frontiers in robotics and AI·2026
查看所有相关文章

相关实验视频

Updated: Jul 6, 2025

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
12:49

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

Published on: July 13, 2019

17.0K

在使用TextWorld的强化学习设置中分解用户定义的任务.

Thanos Petsanis1, Christoforos Keroglou1, Athanasios Ch Kapoutsis2

  • 1School of Engineering, Department of Electrical and Computer Engineering, Democritus University of Thrace (DUTH), Xanthi, Greece.

Frontiers in robotics and AI
|January 8, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了层次增强学习 (HRL),以简化自主代理的复杂任务. 这种方法通过分离行动并实现密集的奖励来增强代理人培训,从而提高整体绩效.

关键词:
自主代理人 独立代理人机器人和自动化中的正式方法.层次化的强化学习学习.强化学习是一种强化学习.任务和运动规划 任务和运动规划

更多相关视频

A Real-world What-Where-When Memory Test
09:13

A Real-world What-Where-When Memory Test

Published on: May 16, 2017

11.3K
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

相关实验视频

Last Updated: Jul 6, 2025

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
12:49

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

Published on: July 13, 2019

17.0K
A Real-world What-Where-When Memory Test
09:13

A Real-world What-Where-When Memory Test

Published on: May 16, 2017

11.3K
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

科学领域:

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

背景情况:

  • 复杂的任务给培训自主代理人带来了重大挑战.
  • 在模拟环境中稀缺的奖励功能往往会阻碍有效的学习.
  • 层次增强学习 (HRL) 为任务分解提供了一个潜在的解决方案.

研究的目的:

  • 建议和评估一种新的等级强化学习 (HRL) 方法用于自主代理培训.
  • 证明任务分解在提高代理学习效率方面的好处.
  • 为了利用高层次的抽象来增强奖励功能设计.

主要方法:

  • 使用TextWorld和MiniGrid Python环境实现一个层次化的强化学习 (HRL) 框架.
  • 使用MiniGrid进行2D环境模拟和TextWorld进行高级任务抽象.
  • 基于任务抽象,为低级环境设计密集的奖励函数.
  • 采用正式方法来验证拟议算法的解决方案寻找能力.

主要成果:

  • 拟议的HRL方法成功地将复杂的任务分解为可管理的子任务.
  • 关于TextWorld抽象的培训使操纵和导航脱而出,简化了学习过程.
  • 与稀疏奖励相比,使用密集奖励函数显著提高了代理人的训练表现.
  • 正式方法证实,该算法能够导出解决方案.

结论:

  • 具有任务抽象的等级增强学习 (HRL) 为培训自主代理提供了有效的策略.
  • 文本世界和MiniGrid的整合促进了HRL的实际和有效实施.
  • 解开行动和使用密集的奖励是提高模拟环境中代理业绩的关键因素.