梯度下降和随机梯度下降_梯度下降和链链接系统
梯度下降和随机梯度下降
On Broken Incentives and Deadlock.
关于激励机制和僵局。
By Shawn Jain and Blake Elias[Shawn Jain is an AI Resident at Microsoft Research.Blake Elias is a Researcher at the New England Complex Systems Institute.]
Shawn Jain和Blake Elias着[ Shawn Jain 是 微软研究中心的 一个 AI驻地 。 布莱克·埃里亚斯 ( Blake Elias) 是 新英格兰复杂系统研究所的研究员。 ]
起源 (Origins)
Several years ago, Blake read “Good Strategy / Bad Strategy: The Difference and Why It Matters”, a book on business and management strategy. Chapter 8, “Chain-Link Systems”, describes situations in which a system’s performance is limited by its weakest sub-unit, or “link”:
几年前，布雷克(Blake)读了一本关于业务和管理策略的书“好的策略/坏的策略：差异及其重要性” 。 第8章，“链式链接系统”，描述了系统性能受其最弱的子单元或“链接”限制的情况：
There are portions of organizations, and even of economies, that are chain-linked. When each link is managed somewhat separately, the system can get stuck in a low-effectiveness state. That is, if you are in charge of one link of the chain, there is no point in investing resources in making your link better if other link managers are not.
组织的各个部分，甚至是经济体，都有部分是连锁的。 当对每个链接进行一些单独的管理时，系统可能会陷入低效状态。 也就是说，如果您负责链中的一个链接，那么如果没有其他链接管理器，则没有必要投入资源来使您的链接更好。
To make matters even more difficult, striving for higher quality in just one of the linked units may make matters worse! Higher quality in a unit requires investments in better resources and more expensive inputs, including people. Since these efforts to improve just one linked unit will not improve the overall performance of the chain-linked system, the system’s overall profit actually declines. Thus, the incentive to improve each unit is dulled. [1]
为了使事情变得更加困难，仅在其中一个链接的单元中争取更高的质量可能会使情况变得更糟！ 一个单元的更高质量要求对包括人力在内的更好的资源和更昂贵的投入进行投资。 由于仅改善一个链接单元的这些努力不会改善链式链接系统的整体性能，因此该系统的整体利润实际上下降了。 因此，改善每个单元的动力减弱了。 [1]
We wondered, how can this idea be made computational? If an organization were run by one or more AI agents, would it be capable of getting past these limitations?
我们想知道，如何将这个想法变成可计算的？ 如果一个组织由一个或多个AI代理运行，它是否能够克服这些限制？
Our intuition is that computation and AI should be able to solve problems where fragmented human organizations get stuck. On the other hand, today’s AI is quite brittle. One failure mode is the existence of local optima.
我们的直觉是，计算和AI应该能够解决零散的人类组织陷入困境的问题。 另一方面，今天的AI相当脆弱。 一种故障模式是局部最优。
It fails to generalize outside its training distribution, and does not form logical representations.
它无法在训练分布范围之外进行概括 ，也没有形成逻辑表示。
问题设定 (Problem Setup)
For a concrete example, consider an assembly line composed of two stations, A and B. Station A takes raw materials and produces a half-finished widget, at a cost of $
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