人工智能ai 学习

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.

如已经讨论的那样， 学习代理可以通过自己从周围环境中学习而无需用户或客户的任何帮助或输入来改善其知识库。

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

在谈论学习代理的元素时 ，以下是其中的主要内容：

• Knowledge Base:

  知识库：

  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.

  知识库是从事人工智能工作的任何代理的基础，因此它必须存在于每个此类系统中。 该知识库中包含所有信息，过去的行为及其影响以及代理工作的各种数据。

• Sensors:

  传感器：

  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.

  为了从环境和周围环境中学习，代理必须能够观察和感知来自环境的信息。 这是通过传感器完成的。 传感器是每个基于AI的代理程序中非常重要的部分，它可以提高其性能并帮助代理程序像人一样工作。

• Processor:

  处理器：

  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.

  处理器(是代理程序的大脑)与计算机的处理器有些相同。 区别在于它比普通处理器先进得多，因为它可以在某些复杂情况下(例如数据不确定性，有关任何任务的信息不完整等)进行处理。这使它在现实生活中的使用效率更高。 而且，代理中的处理器是使代理可以人为操作的处理器。 我们想要在代理中获得更好的性能，应该为此设计更好的处理器。

• Logic Unit:

  逻辑单元：

  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.

  逻辑单元负责在任何决策中绘制和实施逻辑。 代理每次尝试从可用的多个图和语句中得出结果时，都会使用此单元。

• Memory:

  记忆：

  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.

  知识库中存在的所有信息都应存储在某个地方。 因此，对于任何代理来说，内存也是存储所有数据和事实以及由处理器和逻辑单元产生的结果和结论的重要部分。

• Actuators:

  执行器：

  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.

  在所有分析和处理之后，代理必须执行某些操作或产生某些结果。 这由执行器完成。 在机器人技术中，这些执行器是执行某些物理任务的运动部件，而在其他系统中，这些执行器类似于将处理后的数据作为输出生成的输出单元。

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，学习代理还具有许多其他元素，例如硬件，系统设计，电源系统，冷却系统等。

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

人工智能ai 学习