AI knowledge cycle

An Artificial intelligence system has the following components for displaying intelligent behavior:

• Perception
• Learning
• Knowledge Representation and Reasoning
• Planning
• Execution

The above diagram is showing how an AI system can interact with the real world and what components help it to show intelligence. AI system has Perception component by which it retrieves information from its environment. It can be visual, audio or another form of sensory input. The learning component is responsible for learning from data captured by Perception comportment. In the complete cycle, the main components are knowledge representation and Reasoning. These two components are involved in showing the intelligence in machine-like humans. These two components are independent with each other but also coupled together. The planning and execution depend on analysis of Knowledge representation and reasoning.

Approaches to knowledge representation:

There are mainly four approaches to knowledge representation, which are givenbelow:

1. Simple relational knowledge:

• It is the simplest way of storing facts which uses the relational method, and each fact about a set of the object is set out systematically in columns.
• This approach of knowledge representation is famous in database systems where the relationship between different entities is represented.
• This approach has little opportunity for inference.

Example: The following is the simple relational knowledge representation.

2. Inheritable knowledge:

• In the inheritable knowledge approach, all data must be stored into a hierarchy of classes.
• All classes should be arranged in a generalized form or a hierarchal manner.
• In this approach, we apply inheritance property.
• Elements inherit values from other members of a class.
• This approach contains inheritable knowledge which shows a relation between instance and class, and it is called instance relation.
• Every individual frame can represent the collection of attributes and its value.
• In this approach, objects and values are represented in Boxed nodes.
• We use Arrows which point from objects to their values.
• Example:

3. Inferential knowledge:

• Inferential knowledge approach represents knowledge in the form of formal logics.
• This approach can be used to derive more facts.
• It guaranteed correctness.
• Example: Let’s suppose there are two statements:
  1. Marcus is a man
  2. All men are mortal
     Then it can represent as;
     
     man(Marcus)∀x = man (x) ———-> mortal (x)s

4. Procedural knowledge:

• Procedural knowledge approach uses small programs and codes which describes how to do specific things, and how to proceed.
• In this approach, one important rule is used which is If-Then rule.
• In this knowledge, we can use various coding languages such as LISP language and Prolog language.
• We can easily represent heuristic or domain-specific knowledge using this approach.
• But it is not necessary that we can represent all cases in this approach.

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