Artificial Intelligence in General

Artificial Intelligence in General

DOI: 10.4018/978-1-5225-8217-5.ch001

Abstract

There are many kinds of uses for artificial intelligence (AI) in almost every field. AI is quite often used for control, computer aided design (CAD) and computer aided manufacturing (CAM), machine control, computer integrated manufacturing (CIM), production spot control, factory control, intelligent control, intelligent systems, deep learning, the cloud, knowledge bases, database, management, production systems, statistics, to assist sales forces, environment examination, agriculture, art, livings, daily life, etc. The present AI uses will be reexamined whether there is any matter to be considered further or not in AI research directions and their purposes behind the current status by looking at the history of AI development.
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Background

Control in General

In the past, the first significant work in automatic control was James Watt’s centrifugal governor for the speed control of a steam engine in order to control the vapor pressure of the tank in 1788, in England. From this invention, there were various kinds of studies on controls. During the decade of the 1940’s, the frequency-response method made it possible for engineers to design linear feedback control systems that satisfied performance requirements. From the end of the 1940’s to early 1950’s, the root-locus method in control system design was fully developed. These methods are the essence of the classical control. Because of the system to treat many inputs and outputs, these methods became less significant. As the result of this, the modern control theories had been developed from around 1960’s. In the modern control theories, linear control method, non-linear control method, and discrete control method have been developed by the help of computer more and more in the directions of deterministic and stochastic systems, the adaptive system, and learning control of complex systems.

The applications of modern control theories had been expanding quite rapidly to geology, economics, medicine, and sociology. Moreover, with the developing of the micro processors’ process speeds and those kinds of software, it has become possible to have a discrete control and to have expert systems which are able to mimic human skills in manufacturing and in thought of thinking.

Almost in the same period, petri net, neural network, fuzzy logic, genetic algorithm, immune control method, chaos, complexity, and the others have come up to the world as intelligent control methods. Indeed, they were tried to use in complex and huge systems.

Key Terms in this Chapter

Dynamic Knowledge Base: It is simply to make an artifact like a certain kind of human knowledge which is able to understand matter, knowledge, and figure.

OA: Service Oriented Planning.

Deep Learning: It is a branch of machine learning based on a set of algorithms that can be used to model high-level abstractions in data by using multiple processing layers with complex structure, or otherwise composed of multiple non-linear transformations.

Cloud: It has the ability to offer and to assist any kind of useful information without any limitations for users.

SAP: Systems Applications Products (ERP- Enterprise Resource Planning).

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