Expert systems applications, computing

Virtually all tasks which require the routine application of human expertise, in an organized way, are candidates for expert systems. The computer implementation of expertise has such advantages as speed, around-the-clock availability, and ease of expansion of the knowledge base. As such, expert systems represent the next generation of higher level software, performing tasks presently done by human operators. 

The book s first section, on expert systems, is a collection of expert-system applications. Expert systems can simplistically be thought of as computerized clones of an expert in a particular specialty. Various schemes are used to capture the expert s knowledge of the specialty in a manner that the computer can use to solve problems in that field. Expert-systems technology is the most heavily commercialized area in AI as shown by the wide variety of applications that use this technology. These applications help show the breadth of problems to which AI has been applied. Much of the work from other sections of the book also uses expert-system techniques in some manner. 

Bruce A. Hohne and Thomas H. Pierce, Expert System Applications in Chemistry, Developed from a symposium sponsored by the Division of Computers in Chemistry at the 196th National Meeting of the American Chemical Society, Los Angeles, Calif., September 25-30, 1988, in ACS Symposium Series 408, American Chemical Society, Washington, DC, 1989. 

The types of computer programs which have been applied in corrosion engineering and science fall into categories such as (i) conventional software systems (ii) artificial intelligence and expert systems applications (iii) object-oriented software systems ... 

Simply stated, expert systems are computer applications that carry out a degree of logical reasoning similar to those of human beings, making them ideal systems for making subject-matter expertise available to nonexperts (see... 

At present, expert systems in the chemical laboratory are commonly used for separate, interactive applications involving consultations. These expert systems may be described as applying diagnosis or prescription, prediction, monitoring and control, planning, instruction, or interpretation 11). With the development of more powerful software for the microcomputer, there is considerable interest in integrating individual expert system applications into systems which will incorporate the rules of the expert system with numeric computation, database access, and simulation of the chemical reaction or instrumental procedure (2). 

The connectivity of computers to the outside world through the Internet and the Web has opened up tremendous channels of communication that never existed before. This chapter covers a variety of topics related to modeling of corrosion processes, from fundamental expressions to pragmatic models, and to applications of computers such as expert systems and computer-based training. 

The computer has become an accepted part of our daily lives. Computer applications in applied polymer science now are focussing on modelling, simulation, robotics, and expert systems rather than on the traditional subject of laboratory instrument automation and data reduction. The availability of inexpensive computing power and of package software for many applications has allowed the scientist to develop sophisticated applications in many areas without the need for extensive program development. 

Rules seemingly have the same format as IF.. THEN.. statements in any other conventional computer language. The major difference is that the latter statements are constructed to be executed sequentially and always in the same order, whereas expert system rules are meant as little independent pieces of knowledge. It is the task of the inference engine to recognize the applicable rules. This may be different in different situations. There is no preset order in which the rules must be executed. Clarity of the rule base is an essential characteristic because it must be possible to control and follow the system on reasoning errors. The structuring of rules into rule sets favours comprehensibility and allows a more efficient consultation of the system. Because of the natural resemblance to real expertise, rule-based expert systems are the most popular. Many of the earlier developed systems are pure rule-based systems. 

P.G. Raeth, Expert systems a software methodology for modern applications. IEEE Computer Society Press Reprint Collection, IEEE Computer Society Press, Los Alamitos, CA, USA, 1990. 

Expert systems appear in some ways to be the "classic" application of Artificial Intelligence. An expert system is a kind of personal advisor that engages the user in a conversation with the aim of providing help on a specialist topic. In sophisticated systems, the interaction between the expert system (ES) software and the user may be so natural that the user almost forgets that it is a computer rather than a human that is holding up the other end of the conversation. As developers of an ES usually do their best to create software that can participate in "intelligent" conversations, in order to enhance the user s confidence in the system, expert systems can seem the most human and friendly side of AI. 

Expert systems represent a branch of artificial intelligence that has received enormous publicity in the last two to three years. Many companies have been formed to produce computer software for what is predicted to be a substantial market. This paper describes what is meant by the term expert system and the kinds of problems that currently appear amenable to solution by such systems. The physical sciences and engineering disciplines are areas for application that are receiving considerable attention. The reasons for this and several examples of recent applications are discussed. The synergism of scientists and engineers with machines supporting expert systems has important implications for the conduct of chemical research in the future some of these implications are described. 

Until recently, most expert system building took place in the research departments of universities and a few major corporations. The primary emphasis was investigation of artificial intelligence principles, and the application was of secondary importance. The expert systems tools used reflect this interest. They are typically stand-alone AI computer systems, using special hardware and software environments (usually Lispr-based) not commonly fo md in scientific and engineering organizations. 

Computer applications developed from theoretical chemistry tend to be algorithmic and numerical by nature. AI applications tend to be heuristic and symbolic by nature. Multilevel expert systems combine these techniques to use the heuristic power of expert systems to direct numerical calculations. They can also use the results of numerical calculations in their symbolic processing. The problems faced by chemists today are so complex that most require the added power of the multilevel approach to solve them. 

Technology is one of many trends constantly affecting computer validation. One area requiring special attention is the introduction of expert systems into the FDA-regulated environment. The simplest form of artificial intelligence generally used in applications (such as mortgages, credit card authorization, fraud detection, e-commerce, personalization) is the rule-based system, also known as the expert system (ES). 

---