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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
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...
106
Associative Learning01:27

Associative Learning

340
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...
340
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

99
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
99
Resultant of a General Distributed Loading01:13

Resultant of a General Distributed Loading

663
While designing structures exposed to non-uniform loads, it is crucial to consider the resultant force and its location. This resultant force is a single vector representing the net force applied due to the distributed load.
Examples such as load distribution due to wind and load distribution on a bridge illustrate how this concept is used to analyze and design safe, reliable structures under variable loading conditions. Most structures, such as residential buildings, bridges, and towers, are...
663
Dynamic Equilibrium02:20

Dynamic Equilibrium

51.5K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
51.5K
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

528
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...
528

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

Circuits as a simple platform for the emergence of hydrodynamics in deterministic chaotic many-body systems.

Nature communications·2026
Same author

Bounds on Fluctuations of First Passage Times for Counting Observables in Classical and Quantum Markov Processes.

Journal of statistical physics·2025
Same author

Discrete generative diffusion models without stochastic differential equations: A tensor network approach.

Physical review. E·2025
Same author

Exact pretransition effects in kinetically constrained circuits: Dynamical fluctuations in the Floquet-East model.

Physical review. E·2024
Same author

Universal and nonuniversal probability laws in Markovian open quantum dynamics subject to generalized reset processes.

Physical review. E·2024
Same author

Topological phases in the dynamics of the simple exclusion process.

Physical review. E·2024

相关实验视频

Updated: Jun 25, 2025

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

544

结合强化学习和张量网络,与动态大偏差的应用.

Edward Gillman1,2, Dominic C Rose3, Juan P Garrahan1,2

  • 1School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, United Kingdom.

Physical review letters
|May 28, 2024
PubMed
概括

我们介绍了ACTeN,这是一个结合张量网络 (TNs) 和强化学习 (RL) 进行复杂优化的新框架. 这种方法有效地解决了具有挑战性的任务,例如在随机模型中采样罕见事件.

更多相关视频

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

520

相关实验视频

Last Updated: Jun 25, 2025

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

544
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

520

科学领域:

  • 计算物理 计算物理
  • 机器学习 机器学习
  • 统计力学 统计力学

背景情况:

  • 动态优化任务往往涉及大型状态和动作空间,从而带来了重大的计算挑战.
  • 强化学习 (RL),特别是无模型的演员批判方法,为解决这些问题提供了一个强大的范式.
  • 在RL中,传统的函数近似器可以与这些大规模系统的复杂性和维度性作斗争.

研究的目的:

  • 开发一种新的框架,将张量网络 (TN) 方法与强化学习 (RL) 集成在一起,以提高动态优化.
  • 引入"演员-关键与张量网络" (ACTeN) 方法,利用TN进行政策和价值函数近似.
  • 证明ACTeN在计算要求较高的任务中的有效性,包括在随机模型中罕见的轨迹采样.

主要方法:

  • 该研究将张量网络 (TN) 方法作为演员-临界RL算法中的函数近似器集成到研究中.
  • 拟议的"用张量网络进行演员批判" (ACTeN) 方法旨在处理大而可因子化的状态和动作空间.
  • 在东方眼镜模型和不对称的简单排除过程中,ACTeN适用于采样罕见的轨迹.

主要成果:

  • ACTeN 方法成功地解决了在复杂的随机模型中采样罕见轨迹的指数级难题.
  • 该框架在不对称的简单排除过程中表现出特别高的有效性,这种系统对缺乏详细平衡的方法具有挑战性.
  • 结果突出显示了TN对于大规模动态系统的RL中政策和价值函数的近似性.

结论:

  • 该ACTeN框架提供了一个有前途的新方法,通过整合TN和RL来解决具有挑战性的动态优化问题.
  • 这种方法显示出在统计物理学中的应用潜力很大,特别是在模拟罕见事件和复杂系统方面.
  • 整合策略对多代理RL和推进现有RL算法的能力具有广泛的影响.