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相关概念视频

Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.2K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.2K
Entropy02:39

Entropy

34.8K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
34.8K
Entropy01:18

Entropy

3.5K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.5K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

23.9K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
23.9K
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

963
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
963
Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

767
Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
767

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相关实验视频

在强化学习中实现最大度优化的通用稳定.

Xing Chen, Yewen Li, Xiaofeng Cao

    IEEE transactions on neural networks and learning systems
    |November 20, 2025
    PubMed
    概括
    此摘要是机器生成的。

    最大强化学习 (RL) 方法面临稳定性问题. 一个新的β-对称的KL分歧目标稳定了政策和Q功能,改善了RL的性能.

    相关实验视频

    科学领域:

    • 强化学习是一种强化学习.
    • 机器学习理论机器学习理论
    • 决策 决策 决策 决策

    背景情况:

    • 最大强化学习 (RL) 方法提高了稳定性,但存在收困难.
    • 这些问题包括不理想的政策稳定和不稳定的Q值更新,称为"的政策"和"尖的Q功能".

    研究的目的:

    • 为了应对最大的稳定性和收性挑战,RL.
    • 引入一种新的目标函数,减轻的政策和尖的Q函数.

    主要方法:

    • 在最大框架内引入了一个β-对称的Kullback-Leibler (KL) 差异目标.
    • 开发了一种称为最大稳定优化 (MeSO) 的方法,涉及代的Q值和政策更新.
    • 在目标Q值中化,以避免尖的Q函数.

    主要成果:

    • 贝塔对称的KL差异目标控制了具有大贝塔值的政策震荡.
    • 将新的目标函数最小化在理论上提高了Q值.
    • 在实验中,MeSO表现出稳定性,灵活性,并提高了整体性能.

    结论:

    • 拟议的β-对称的KL差异目标有效地稳定了最大值RL.
    • 对于现实世界的决策任务,MeSO提供了一个强大而高性能的替代方案.
    • 该方法改进了现有的最大率RL方法.