Introduction

An expert system is a computer application that solves complicated problems that would otherwise require extensive human expertise. To do so, it simulates the human reasoning process by applying specific knowledge and interfaces. Expert systems also use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Books and manual guides have a tremendous amount of knowledge but a human has to read and interpret the knowledge for it to be used.

A system that uses human knowledge captured in a computer to solve problems that ordinarily require human expertise (Turban & Aronson, 2001).

A computer program designed to model the problem solving ability of a human expert (Durkin, 1994).

An intelligent computer program that uses knowledge and inference procedures to solve problems that was difficult enough to acquire significant human expertise for their solutions (Feigenbaum).

Expert systems typically have a number of several components. The knowledge base is the component that contains the knowledge obtained from the domain expert. Normally the way of representing knowledge is using rules. The inference engine is the component that manipulates the knowledge found in the knowledge base as needed to arrive at a result or solution. The user interface is the component that allows the user to query the system and receive the results of those queries. Many ES's also have an explanation facility which explains why a question was asked or how a result or solution was obtained.

There are several major application areas of expert system such as agriculture, education, environment, law manufacturing, medicine power systems etc. In this article we will review about agriculture, education, environment and medicine expert system.  These four applications widely use among the practitioners due to the maturity of the field by revealing the acceptance of the technology by the commercial sectors. 

هوش مصنوعی:

هوش مصنوعی روشی است در جهت هوشمند کردن کامپیوتر تا قادر باشد در هر لحظه تصمیم گیری کرده و اقدام به بررسی یک مسئله نماید. هوش مصنوعی، کامپیوتر را قادر به تفکر می کند و روش آموختن انسان را تقلید می نماید. بنابراین اقدام به جذب اطلاعات جدید جهت بکارگیری مراحل بعدی می پردازد.

مغز انسان به بخش هایی تقسیم شده است که هر بخش وظیفه خاص خود را جدا از بقیه انجام می دهد. اختلال در کار یک بخش تاثیری در دیگر قسمت های مغز نخواهد گذاشت. در برنامه های هوش مصنوعی نیز این مسئله رعایت      می شود درحالی که در برنامه های غیر هوش مصنوعی مثل C یا Pascal تغییر در برنامه روی سایر قسمت های برنامه و اطلاعات تاثیر دارد.

مباحث کاربردی و مهم در تحقق یک سیستم هوش مصنوعی :

1-     سیستم های خبره(Expert Systems)

2-     شبکه های عصبی(Neural Network)

3-     الگوریتم های ژنتیک(Genetic Algorithms)

4-     سیستم های منطق فازی(Fuzzy Logic Systems)