Knowledge Representation in Artificial Intelligence | Types| Schemes| Full Info

Knowledge Representation in Artificial Intelligence

knowledge representation in artificial intelligence
knowledge representation in artificial intelligence

The knowledge of determination does not easily increase the provision of an A. knowledge of the mechanisms at work in full who is manipulating the art. To work it follows that the knowledge of the knowledge of the streets, neither have entered into the machinations of the chosen of God. It ‘s better to the example of his logical thinking of the representation of the machinations of the investigation on the part of some. However, the 2 points for representing knowledge.

The representation of the subarea is an “artificial intelligence knowledge” to understanding, designing and implementing the simplest way is representing a distinct data and information that can be used by a computer program.

Artificial intelligence, the reason is, that the understanding of this can be involved with the study, succeeded when him, and as a fruit, and also the ways that of implementing the work with the knowledge of his mission with computers.

In any intelligent system, which suggests science may be an important technique to encode knowledge.

The main objective is to design programs that give info to the computer system of AI that will be helpful to interact with individuals in various fields and solve issues that require human intelligence.

Advanced Knowledge Representation Techniques in Artificial Intelligence

This video from Well Academy Youtube channel

Types of Knowledge Representation in Artificial Intelligence

1. Procedural knowledge

Procedural knowledge is compiled or processed within the data type. Procedural knowledge is related to the performance of some task. For example, the sequence of steps to solve a problem is that knowledge of the procedures.

2. Declarative knowledge

Declarative knowledge is passive knowledge in the form of statements of facts about the world. For example, the declaration of a student’s brand is declarative knowledge.

3. Heuristic knowledge

Heuristic knowledge is golden rules or tricks. Heuristic knowledge is used to formulate judgments and, in addition, to modify the resolution of problems. It is acquired through experience. A professional uses the knowledge he has gathered due to his experience and learning.

4. Importance of knowledge.

Intelligence needs knowledge. That is, to exhibit intelligence, knowledge is needed. Knowledge plays a very important role in the construction of intelligent systems.

5. Meta-knowledge

This type provides an idea with respect to the opposite types of knowledge that are adequate to solve a problem.
Meta-knowledge is useful to improve the efficiency of problem-solving through an adequate reasoning process.

6. Structural knowledge

Structural knowledge is associated with information based on rules, sets, concepts and relationships.
It provides the necessary information to develop knowledge structures and also the general mental model of the problem.

Knowledge Representation Schemes in Artificial Intelligence

The knowledge representation schemes are useful only if there are functions that relate the facts to the representations and vice versa. AI is more concerned with representation in the natural language of facts and functions that map natural language sentences in some representational formalism. An attractive way to represent facts is to use the language of logic. The logical formalism provides a way to derive new knowledge of the old through mathematical deductions. In this formalism, we can conclude that a new statement is true by demonstrating that it follows from statements already known as facts.

The representation of knowledge (KR) due to the origin of a subfield of artificial intelligence (AI). within the First Days of the AI, in general, he imagined himself sufficiently to provide a dark and rational capacity for the computer reasoning of intelligence Seria A pure; However, it became clear that the exercise of intelligence comprised the interaction of the World Inevitably Inevitably with AN, such interaction and can not have a certain knowledge of that place, the sin of the world.

Therefore, it is clear that a part of the knowledge dopant’s search for Dębe’s methods referred to the development of computer systems. To be once your, SE of As put of the Question to alleviate the knowledge between the computer represented.

This QUESTION can be addressed in many other ways, one of which, however, will distinguish widely between the Approaches that you will find and, most, the Vertue of, knowledge representation in artificial intelligence the ways in which the Knowledge Direction is represented in the line of the Human brain and those who are inspired by the type of representation outside. used by humans for coding the knowledge of the pig, in particular, the mathematical language and formal logic.

The term knowledge representation (KR), when we are in the context of the AI, is usually taken to prepare the associated approach of this type, the last fourth of the primary, which is considered much within the science of knowledge.

Explain Knowledge Representation Advantage and  Disadvantages in artificial intelligence

Knowledge Representation Advantage

  • Easy to understand and visualize.
  • Facilitates programming by grouping related data.
  • Similar to human language.
  • It is flexible
  • Easy to configure slots for new properties and relationship.
  • The expressive power.

Knowledge Representation Disadvantages

  • There are no rules.
  • Very generalized approach.

  • The inference mechanism is not easy to proceed.

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