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相关概念视频

Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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Machines: Problem Solving I01:22

Machines: Problem Solving I

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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...
356
Machines: Problem Solving II01:30

Machines: Problem Solving II

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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.
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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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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.
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相关实验视频

Updated: Jul 22, 2025

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一个自我学习的蒙特卡洛树搜索算法用于机器人路径规划.

Wei Li1, Yi Liu1, Yan Ma1

  • 1Academy for Engineering and Technology, Fudan University, Shanghai, China.

Frontiers in neurorobotics
|July 24, 2023
PubMed
概括

本研究介绍了一种自学蒙特卡罗树搜索 (SL-MCTS) 算法,该算法可以增强单人游戏中的问题解决能力. 与传统方法相比,SL-MCTS显著提高了路径质量,并减少了时间消耗.

关键词:
马尔科夫决策过程 (MDP)蒙特卡洛树搜索 (MCTS) 是一个集体智能算法集体智能算法神经网络的神经网络的神经网络路径规划路径规划路径规划

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科学领域:

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

背景情况:

  • 蒙特卡罗树搜索 (MCTS) 是一种常见的算法,用于复杂问题的决策.
  • 传统的MCTS在单一玩家场景中可能是低效的,需要提高融合速度和搜索效率.
  • 现有的路径规划算法往往缺乏持续自我改进的能力.

研究的目的:

  • 提出一种新的自学MCTS算法 (SL-MCTS),以提高单人场景中的性能.
  • 通过使用神经网络来提高MCTS的融合速度和搜索效率.
  • 通过自我学习,不断提高解决问题的能力.

主要方法:

  • 开发了一个自学蒙特卡罗树搜索 (SL-MCTS) 算法.
  • 集成了一个双分支神经网络 (PV-Network) 来预测搜索方向和节点值,取代了MCTS推出过程.
  • 实施了一种自我学习机制,将当前模型性能与历史最佳模型进行比较,以指导优化.

主要成果:

  • 与传统的MCTS和单人MCTS相比,SL-MCTS在机器人路径规划方面表现出卓越的表现.
  • 与传统的MCTS相比,实现了显著更好的路径质量和更低的时间消耗,时间消耗减少了一半.
  • SL-MCTS的性能与用于路径规划的专用代搜索算法相当.

结论:

  • SL-MCTS提供了一种强大而高效的方法,用于单人解决问题,特别是在路径规划中.
  • 光伏网络和自我学习的整合显著提高了MCTS的融合和效率.
  • SL-MCTS提供了一个可扩展的解决方案,用于在复杂的决策任务中不断改进.