人工智能ai 學習

As already discussed, the Learning agents have the capability to improve their knowledge base by Learning from their surroundings by themselves, without any help or input from the user or the client.

如已經討論的那樣， 學習代理可以通過自己從周圍環境中學習而無需用戶或客戶的任何幫助或輸入來改善其知識庫。

When talking about the elements of the Learning agent, the following are the major of them:

在談論學習代理的元素時 ，以下是其中的主要內容：

• Knowledge Base:

  知識庫：

  The Knowledgebase is the fundamental part of any agent which works on Artificial Intelligence and thus it has to be present inside every such system. All the information, past actions, and their impacts, and all sorts of data that the agent works on is present inside this Knowledge Base.

  知識庫是從事人工智能工作的任何代理的基礎，因此它必須存在于每個此類系統中。 該知識庫中包含所有信息，過去的行為及其影響以及代理工作的各種數據。

• Sensors:

  傳感器：

  For Learning from the environment and the surroundings, the agent must be able to observe and perceive information from the environment. This is done through the sensors. The sensors form a very crucial part of every AI based agent in improving its performance and helping the agent to act like a human.

  為了從環境和周圍環境中學習，代理必須能夠觀察和感知來自環境的信息。 這是通過傳感器完成的。 傳感器是每個基于AI的代理程序中非常重要的部分，它可以提高其性能并幫助代理程序像人一樣工作。

• Processor:

  處理器：

  The processor, which is the brain of the agent is somewhat the same as the processor of a computer. The difference is that it is much more advanced than the normal processors as it can process in certain complex situations also such as uncertainty in data, incomplete information about any task, etc. This makes it much more efficient to use in real life situations. Also, the processor in the agent is the one which makes an agent can humanly. The better performance we want in our agent, the better processor should be designed for it.

  處理器(是代理程序的大腦)與計算機的處理器有些相同。 區別在于它比普通處理器先進得多，因為它可以在某些復雜情況下(例如數據不確定性，有關任何任務的信息不完整等)進行處理。這使它在現實生活中的使用效率更高。 而且，代理中的處理器是使代理可以人為操作的處理器。 我們想要在代理中獲得更好的性能，應該為此設計更好的處理器。

• Logic Unit:

  邏輯單元：

  The Logic Unit is responsible for drawing and implementing the logic in any decision. This unit comes into use every time the agent tries to conclude the results from the multiple figures and statements available.

  邏輯單元負責在任何決策中繪制和實施邏輯。 代理每次嘗試從可用的多個圖和語句中得出結果時，都會使用此單元。

• Memory:

  記憶：

  All the information which is present inside the Knowledge Base should be stored somewhere. So, Memory is also an important part for any agent to store all the data and facts, and the results and the conclusions which are produced by the processor and the logic unit.

  知識庫中存在的所有信息都應存儲在某個地方。 因此，對于任何代理來說，內存也是存儲所有數據和事實以及由處理器和邏輯單元產生的結果和結論的重要部分。

• Actuators:

  執行器：

  The agent must perform certain actions or produce some result after all the analysis and processing. This is done by the actuators. In robotics, these actuators are the moving parts which perform certain physical tasks, whereas, in other systems, these are similar to output units which produce the processed data as the output.

  在所有分析和處理之后，代理必須執行某些操作或產生某些結果。 這由執行器完成。 在機器人技術中，這些執行器是執行某些物理任務的運動部件，而在其他系統中，這些執行器類似于將處理后的數據作為輸出生成的輸出單元。

Apart from these, there are also many other elements of the Learning Agent like the Hardware, Design of the system, power system, cooling systems, etc.

除此之外，學習代理還具有許多其他元素，例如硬件，系統設計，電源系統，冷卻系統等。

翻譯自: https://www.includehelp.com/ml-ai/elements-of-a-learning-agent-in-artificial-intelligence.aspx

人工智能ai 學習

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