A First Course in Artificial Intelligence

Every beginner in any subject needs a good foundation, which will help the student to understand the subject. This good foundation will be provided in a thorough and detailed definition of the subject and a detailed description of the fundamental models on which the subject is based. Artificial Intelligence needs a thorough definition and a detailed description of the fundamental models on which Artificial Intelligence is based. Furthermore, the history and applications of Artificial Intelligence will help the beginner to know where it is coming from, the journey so far, and the future development of Artificial Intelligence. On the other hand, the applications of Artificial Intelligence will help us to appreciate the use of Artificial Intelligence in our daily life. This chapter presents a detailed definition of Artificial Intelligence, its history, and emerging applications.

Knowledge representation and automated reasoning are part of the attributes of an intelligent system. These two attributes are used to form the two main components of an expert system, which are the knowledge base and inference engine. Since Artificial Intelligence deals with the study and design of a system that acts like a human, therefore, studying and designing a system that acts like a human expert in any profession qualifies to be called Artificial Intelligence.

The ability to communicate in natural language remains one of the qualities of an intelligent system. The aspect of Artificial Intelligence that deals with this quality of an intelligent system is natural language processing. This chapter considers this aspect of Artificial Intelligence in detail.

All discoveries made by man in any discipline, like physical sciences, biological sciences, social sciences, engineering, etc., are based on past experiences or collected data. This means that human beings solve the problem by using past experiences or collected data. Therefore, since one aspect of Artificial Intelligence, as pointed out in chapter 1, unit 1, is to design systems that act like man, it becomes necessary that computer systems should be designed to solve the problem the way human beings solve a problem. This means that computer systems should be designed to solve the problem using past experience or previously stored data. The data are called training data because they are used to train the computer to learn the trend or pattern of the training data. Learning the pattern or trend of the training data as a rule, it uses the learnt rule to solve a subsequent problem using test data that has the same structure as the training data. The vast amount of data in machine learning is divided into two sets, which are the training set and the test set. The training set is used to develop a model, while the test set is used to evaluate the performance of the model. Data splitting technique in machine learning refers to the technique used to split the data into a training set and test set. The aim is to avoid poor generalization, i.e., overfitting or overtraining. Using more training sets improves the accuracy of the model, while using more test data improves the accuracy of the error estimate. An appropriate training/test set ratio of 70:30 is considered appropriate. Machine learning, therefore, is an aspect of Artificial Intelligence that deals with the design of systems that uses a large set of data called training data to solve a particular problem. Machine learning is a broad area in Artificial Intelligence, which will be considered in the various units of this chapter.

Most machine learning tools are applied to different areas to solve specific problems. This involves the use of a large dataset as training data. This chapter explores selected applications of machine learning algorithms to solve different problems using different datasets.

One of the qualities of an intelligent system is perception ability. It refers to the ability that provides information to agents using sensors. Human beings have five main sensory organs, which include: sense organ of hearing, vision, tasting, feeling, and smelling. Therefore, to act like man, which means to possess the attributes of an intelligent system, the system must have the ability to perceive the outside world it inhabits using the five sensors, ear, eye, tongue, skin, and nose. The following sensors have been developed in artificial agents, which they share with human sense organs: vision, hearing, and touch. This chapter focuses on these three sensors of an artificial agent.

One of the qualities of an intelligent system is the ability to move an object from one place to another. This quality leads to the study of Robotics, which is the aspect of Artificial Intelligence that deals with the study and design of robots. An autonomous robot is a robot that makes decisions on its own, and it shares many things in common with an autonomous vehicle or self-driving vehicle.