Abstract
In the realm of artificial intelligence, knowledge representation is a vital
aspect that enables effective information sharing and processing. Humans excel at
sharing trusted information, which is acquired through rigorous testing and validation,
resulting in what we commonly refer to as knowledge. The representation of
knowledge can take various forms, such as graphs, maps, or textual formats. With the
continuous evolution of the IT sector, the introduction of AI has simplified many tasks,
often surpassing human capabilities and effortlessly handling even the most basic
activities. However, understanding the concept of knowledge representation remains a
fundamental question. In this research paper, we delve into the basics of knowledge
representation to directly address this question. The understanding of knowledge
representation is best achieved by examining the role knowledge plays in specific case
studies or systems, which includes scientific reasoning and comprehension of the
world. By exploring the intricacies of knowledge representation, we aim to provide a
practical approach to its implementation in the field of artificial intelligence.