Artificial Intelligence-Based Knowledge Representation and Reasoning

Artificial Intelligence-Based Knowledge Representation and Reasoning

Dimpal Tomar, Pradeep Tomar
DOI: 10.4018/978-1-7998-4763-2.ch008
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Abstract

The quality of higher education can be enhanced only by upgrading the content and skills towards knowledge. Hence, knowledge representation and reasoning play a chief role to represent the facts, beliefs, and information, and inferring the logical interpretation of represented knowledge stored in the knowledge bases. This chapter provide a broad overview of knowledge, representation, and reasoning along with the related art of study in the field of higher education. Various artificial intelligent-based knowledge representation and reasoning techniques and schemes are provided for better representation of facts, beliefs, and information. Various reasoning types are discussed in order to infer the right meaning of the knowledge followed by various issues of knowledge representation and reasoning. .
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1. Introduction

Intelligence is one of the complex phenomena as stated by the individuals that is clearly governed by the knowledge. For example, a person can take a decision about what has to do on the basis of what we believe or no effortlessly. Artificial Intelligence (AI) is the study of intelligence and behaviour governed by the machines through computational means in contrast to natural intelligence.In artificial intelligence, knowledge representation and reasoning act as a central aspect which is concerned with how a machine represent a human knowledge and use it in order to decide what to do.

Knowledge representation and reasoning plays a vital role in several domain of learning, teaching and research. For instance, in higher education, development of an intelligent educational system and intelligent tutoring system encompassing intelligences by offering adaptive representation and navigation of teaching contents. The crucial aspect while developing the system is how knowledge has to be represented and how the meaning is accomplished for making decisions (Hatzilygeroudis & Prentzas, 2006).

This section will try to address an overview on understanding what is knowledge, representation and reasoning.Why these concepts are important in artificial intelligence followed by the artificial intelligence knowledge cycle.

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