1.1 Introduction
An Artificial Intelligence (AI) program is called Intelligent Agent. Intelligent agent gets to interact with the environment. The agent can identify the state of an environment through its sensors and then it can affect the state through its actuators. The important aspect of AI is the control policy of the agent which implies how the inputs obtained from the sensors are translated to the actuators, in other words how the sensors are mapped to the actuators, this is made possible by a function within the agent. The ultimate goal of AI is to develop human like intelligence in machines. However such a dream can be accomplished through learning algorithms which try to mimic how the human brain learns. Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data.
As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Research hypothesis and questions, Limitations of the Study and Definition of technical terms.
1.2 Background of Study
The initiative for developing Artificial Intelligence (AI) system starts in the 1950 year. With the appearance of the initiative there is also the appearance of several doubts about its application and its usage. So, scepticism as the result have so-called AI winter which in a significant way decrease the speed of the developing AI. At the beginning of the development of AI, there is a challenge related to the lack of computer systems as well as computer technologies. Furthermore, there is also a challenge related to the speed of such systems that are not good enough. With the development of computer science and computers as a whole, the development of AI is increasing. The first usage of AI was in the United States Department of defense in which the main usage of the AI system was collecting and analyzing large amounts of data. In the 1990 year, AI was used in the game industry. This year is also a pivotal year for AI and its popularity because AI chess software showed that it can win against humans in the chess game.
Machine learning, which is a field that had grown out of the field of artificial intelligence, is of utmost importance as it enables the machines to gain human like intelligence without explicit programming. However AI programs do the more interesting things such as web search or photo tagging or email anti-spam. So, machine learning was developed as a new capability for computers and today it touches many segments of industry and basic science. There is autonomous robotics, computational biology. Around 90% of the data in the world was generated in the last two years itself and the inclusion of machine learning library known as Mahout into Hadoop ecosystem has enabled to encounter the challenges of Big Data, especially unstructured data.
AI is a new scientific discipline which is aimed at creating new theories, mechanisms and creating new application and possibilities of AI-based creating systems that are similar to the human and inelegance that is similar to them. As science discipline, AI includes different kinds of systems that have characteristics similar to humans and also systems that are, in the context of the behavior, similar to humans. Furthermore, AI includes systems that have rational thinking and also systems that are created to look like humans (Putica, 2018).
It seems surprising that despite of the frequent use of the terms, there is hardly any helpful scientific delineation. Thus, this paper aims to shed light on the relation of the two terms machine learning and artificial intelligence. We elaborate on the role of machine learning within instantiations of artificial intelligence, precisely within intelligent agents. To do so, we take a machine learning perspective on the capabilities of intelligent agents as well as the corresponding implementation.
Therefore, in Nigeria where the research was carried out, the activities that was conducted is to know the Role of Machine Learning in Artificial Intelligence.
1.3 Statement of Problems
Investigation reveals that the number one problem facing Machine Learning is the lack of good data. While enhancing algorithms often consumes most of the time of developers in AI, data quality is essential for the algorithms to function as intended. Noisy data, dirty data, and incomplete data are the quintessential enemies of ideal Machine Learning. It's becoming increasingly difficult to separate fact from fiction in terms of Machine Learning today. Before you decide on which AI platform to use, you need to evaluate which problems you’re seeking to solve. The easiest processes to automate are the ones that are done manually every day with no variable output. Complicated processes require further inspection before automation. While Machine Learning can definitely help automate some processes, not all automation problems need Machine Learning (Provintl, 2021).
1.4 Aim and Objectives of Study
The aim of the study is to examine the Role of Machine Learning in Artificial Intelligence. In achieving this aim, the following specific objectives were laid out as follows:
- To examine the relevance of Machine Learning in Artificial Intelligence programs.
- To investigate the relationship between Machine learning and Artificial Intelligence during application programming.
- To investigate the computer simulation of human learning processes.
- To analyze the learning systems oriented toward solving a predetermined set of tasks (also known as the “engineering approach”).
1.5 Research Questions
The study came up with research questions so as to be able to ascertain the above stated objectives. The specific research questions for the study are stated below as follows:
- Is there any significant relationship between Machine learning and Artificial Intelligence during application programming?
- What is the relevance of Machine Learning in Artificial Intelligence programs?
- What are the human learning processes of computer simulation?
- What is the learning systems oriented toward solving a predetermined set of tasks?
1.6 Significance of Study
Machine learning can prove immensely helpful in the process of building an information time machine. This study will be of immense benefit to software engineers and other researchers who intend to know more on this study and can also be used by non-researchers to build more on their research work. This study contributes to knowledge and could serve as a guide for other study.
1.7 Scope of Study
The scope of the research is focused on the Role of Machine Learning in Artificial Intelligence.
1.8 Limitations of the Study
During the course of this study, many things militated against its completion, some of which are:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Research material: availability of research material is a major setback to the scope of the study.
- Frequent power failure: This made the researcher append more money on fuel to ensure sustainable power.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection.
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