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Knowledge Representation

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Human beings are good at understanding, reasoning, and interpreting knowledge. And using this knowledge, they are able to perform various actions in the real world.
But how do machines perform the same?!

KR in AI describes the representation of knowledge. Basically, it is a study of how the beliefs, intentions, and judgments of an intelligent agent can be expressed suitably for automated reasoning. Knowledge Representation and Reasoning (KR, KRR) represents information from the real world for a computer to understand and then utilize this knowledge to solve complex real-life problems like communicating with human beings in natural language.
There are four techniques for representing knowledge such as:
Logical Representation, Semantic Network Representation, Frame Representation, and Production Rules.

We can best represent your information in a specific domain for a computer and prepare it for automated reasoning.

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