Everything about Knowledge Representation in Intelligent Automation

Artificial intelligence is a broad subject and it requires you to perform plenty of complex tasks. The whole aspect is divided into two major parts and they are machine learning and deep learning. There is a necessity to automate a knowledge process for this system. This is precisely where the concept of knowledge representation comes in play. The knowledge representation in AI is a system, which depends a lot on logical situations. As a human being you acquire various types of knowledge, but machines find them hard to interpret. This is precisely the reason for knowledge representation to be a force today. 

The algorithmic are a major force in knowledge representation and artificial intelligence agents are of the opinion that they can make a valuable contribution. Let us discuss in detail about knowledge representation issues in artificial intelligence

A look at the varied representation of knowledge: 

These are some of varied types of knowledge, which need to be represented in the AI systems. 

  1. Events: An event is best described as an occurrence of something in a real world. If the development has unfolded in real time, it is considered as an event. 
  2. Object: This is nothing but material facts, which are actually true. Such facts can be universal and let us take the example of the sun rising in the east. 
  3. Meta Knowledge: As we discuss more about types of knowledge representation in artificial intelligence, the meta knowledge surely comes to the forefront. This is specific knowledge, which has been acquired previously by human brains or machines. 
  4.  Knowledge base: This is best described as the core component of the agents acquiring the knowledge. 
  5. Performance factor; This gives an insight into how well the knowledge has been acquired and whether you can apply the knowledge representation techniques into machines. 

An insight into the various categories of knowledge: 

There is also the scope to categorize the knowledge and this is divided into two basic types. Let me take you through the variety. 

  • The first is tactical knowledge and it exists within a human being. There is correspondence to informal or implicit forms of knowledge. 
  • The other option is the explicit form of knowledge and they exist outside a human being. This version corresponds to a formal type of knowledge. 

What precisely are the requirements of knowledge representation? 

There are certainly requirements for a knowledge representation program and let me update you in brief.

  1. There is a need to have adequacy or fulfillment to represent all types of knowledge in the domain. One may also refer it to representational adequacy. 
  2. It should boast of a capability to manipulate the representational structures in the quest to derive new better structures. These new structures need to correspond to the new knowledge. 
  3. There should also be the capacity to include additional information into the knowledge structure. This is used to focus on interference mechanisms in the best possible way. 
  4. The new knowledge must be acquired by automated methods rather than relying upon the traditional human source. 

We have looked to offer you an in-depth analysis on knowledge representation in intelligent automation. This should prove useful to you.

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