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

Reinforcement Schedules01:24

Reinforcement Schedules

135
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,...
135
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45
Limits to Natural Selection01:38

Limits to Natural Selection

31.2K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
31.2K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.0K
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...
3.0K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

101
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
101
Randomized Experiments01:13

Randomized Experiments

6.8K
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...
6.8K

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

Parrondo's paradox as a framework for strategy switching and collective intelligence in complex systems Reply to comments on "Parrondo's paradox reveals counterintuitive wins in biology and decision making in society".

Physics of life reviews·2026
Same author

DAFRL: a dynamic adaptive mean field game-based multi-agent cooperative decision-making method.

Scientific reports·2026
Same author

Adaptive Prescribed-Time Dynamic Self-Triggered Time-Varying Bipartite Formation Control for Uncertain Nonlinear Multiagent Systems With Actuator Faults.

IEEE transactions on cybernetics·2026
Same author

Event-Triggered Safety-Stability Framework for Learning-Based Control of Multiagent System With Uncertain Dynamics.

IEEE transactions on cybernetics·2026
Same author

Prescribed performance collision-free control for bearing-constrained unmanned aerial vehicle.

ISA transactions·2025
Same author

ZO-1/Tjp1 and ZO-2/Tjp2 deletion in retinal pigment epithelium causes progressive retinal degeneration.

iScience·2025

相关实验视频

Updated: Jun 12, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.6K

通过强化学习在复杂网络上进行持续战略游戏的最佳进化策略.

Litong Fan, Dengxiu Yu, Kang Hao Cheong

    IEEE transactions on neural networks and learning systems
    |September 20, 2024
    PubMed
    概括

    本研究介绍了通过强化学习 (RL) 在网络上进行连续游戏的适应性策略. 它使代理商能够以最小的战略变化实现最佳合作,增强进化游戏理论.

    科学领域:

    • 游戏理论 游戏理论
    • 人工智能的人工智能
    • 网络科学 网络科学

    背景情况:

    • 传统的进化游戏理论假设单一的代理学习强度,忽视个人差异.
    • 代理商经常表现出不愿意显著改变战略,限制合作水平.

    研究的目的:

    • 开发适应性战略更新框架,用于复杂网络上的连续游戏.
    • 为了使代理商能够以最少的战略修改实现最佳状态和更高的合作.

    主要方法:

    • 一个基于模仿动态的适应性框架,具有不同的选择强度.
    • 结合汉密尔顿 - 雅各比 - 贝尔曼 (HJB) 方程,通过最小化性能函数来导出最佳策略更新.
    • 一个值代 (VI) 强化学习 (RL) 算法,使用演员关键神经网络来近似HJB解决方案.

    主要成果:

    • 拟议的RL算法有效地学习最佳战略更新规则.
    • 方法的稳定性和收性用莱普诺夫函数数学证明.
    • 模拟证实了各种游戏和网络结构的有效性和融合.

    结论:

    • 适应性战略框架增强了复杂网络游戏中的合作.

    更多相关视频

    Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER
    07:26

    Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

    Published on: May 19, 2019

    11.9K
    New Variations for Strategy Set-shifting in the Rat
    09:45

    New Variations for Strategy Set-shifting in the Rat

    Published on: January 23, 2017

    8.2K

    相关实验视频

    Last Updated: Jun 12, 2025

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
    11:53

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

    Published on: October 14, 2017

    11.6K
    Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER
    07:26

    Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

    Published on: May 19, 2019

    11.9K
    New Variations for Strategy Set-shifting in the Rat
    09:45

    New Variations for Strategy Set-shifting in the Rat

    Published on: January 23, 2017

    8.2K
  • 强化学习为解决连续战略游戏提供了一种有效的方法.
  • 最小的战略变化导致最佳结果和更高的合作水平.