ai人工智能在手機的應用

The reinforcement learning is being used in many Intelligent Systems and the developers are seeing a great scope in it for current and future developments in the field of computers and robotics. This is because, the Reinforcement Learning till now is the most effective and simple way to make a computer system think, learn and act humanely. Due to this reason, this has been a field of attraction for the computer and industrial world. Some major projects which use this concept in their systems have already been developed and launched, and some are still under development. Due to more work output than humans in laborious works, such systems are high in demand in the industrial sectors.

強化學習已在許多智能系統(tǒng)中使用，并且開發(fā)人員看到其中的擴展范圍適用于計算機和機器人技術領域的當前和未來發(fā)展。 這是因為，到目前為止，強化學習是使計算機系統(tǒng)進行人性化思考，學習和行動的最有效，最簡單的方法。 由于這個原因，這已成為計算機和工業(yè)界的一個吸引領域。 已經開發(fā)并啟動了一些在其系統(tǒng)中使用此概念的大型項目，而某些仍在開發(fā)中。 由于辛勤勞動中的勞動產出大于人類勞動，因此這種系統(tǒng)在工業(yè)領域中的需求很高。

強化學習的應用 (Applications of Reinforcement Learning)

Reinforcement Learning finds its applications in the following areas:

強化學習在以下領域有其應用：

• Used in robotics for Industrial automation:

  用于工業(yè)自動化機器人：

  Most of the industries require man force either as laborers, workers or supervisors. Most of these have the same routine to follow each day and they have to work in the same manner in which they have been escorted. The robots designed to do such type of tasks prove to be more beneficial than humans as they do not require rest and they can be used for unlimited working hours. So, despite that, it makes thousands of people jobless, yet businessmen and great industry men chose the robots over humans for earning more profit.

  大多數(shù)行業(yè)都需要勞動力，無論是工人，工人還是主管。 這些大多數(shù)每天都有相同的例行程序，并且必須以陪同方式工作。 事實證明，設計用于執(zhí)行此類任務的機器人比人類更有利，因為它們不需要休息，并且可以無限次地使用。 因此，盡管如此，它仍然使成千上萬的人失業(yè)，但是商人和偉大的商人選擇了機器人而不是人類，以賺取更多的利潤。

• Used in Machine Learning:

  用于機器學習：

  Reinforcement Learning is one of the major topics in Machine Learning and is currently in trend and is a major source of attraction for many researchers and developers.

  強化學習是機器學習的主要主題之一，并且目前處于趨勢中，并且是吸引許多研究人員和開發(fā)人員的主要來源。

• Used in creating training systems and self-operating systems:

  用于創(chuàng)建培訓系統(tǒng)和自我操作系統(tǒng)：

  reinforcement learning is being used to create different self-operating systems like self-driving cars, automated arms, House cleaning agents, etc. Apart from these, many training systems are also designed using it like the test conducting systems, systems which are able to have a human-like communication, systems which are able to receive any call and reply as per the going conversation, etc.

  強化學習被用于創(chuàng)建不同的自我操作系統(tǒng)，例如自動駕駛汽車，自動手臂，房屋清潔劑等。除這些之外，還設計了許多培訓系統(tǒng)，例如測試執(zhí)行系統(tǒng)，擁有類似于人的交流能力，能夠根據(jù)正在進行的對話接收任何呼叫和回復的系統(tǒng)，等等。

• Used in Data Processing:

  用于數(shù)據(jù)處理：

  In Intelligent agents and expert systems which work in a dynamic and partially observable environment, the reinforcement learning is an effective and widely used way for Data Processing, as the conditions with uncertainty can be easily handled using it.

  在動態(tài)的且部分可觀察的環(huán)境中工作的智能代理和專家系統(tǒng)中，強化學習是一種有效且廣泛使用的數(shù)據(jù)處理方式，因為不確定性條件可以使用它輕松處理。

Apart from this, there are still many uncovered areas where the Reinforcement Learning finds its application and there are also areas where the research and implementation process of the same is being performed.

除此之外，強化學習仍在許多未發(fā)現(xiàn)的領域找到了應用，并且還進行了研究和實施過程。

翻譯自: https://www.includehelp.com/ml-ai/applications-of-reinforcement-learning-in-artificial-intelligence.aspx

ai人工智能在手機的應用

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