What is an expert system?
Nowadays the Expert Systems (SE) can be considered as a subset of the AI. An Expert System is a system that uses human knowledge obtained in a computer to solve problems that would normally be solved by expert humans. Well-designed systems mimic the reasoning process that experts use to solve specific problems. These systems can work better than any human expert making decisions individually in certain domains and can be used by non-expert humans to improve their problem-solving skills.
Expert systems can be considered as the beginning of artificial intelligence. They were developed by the AI community in the mid-60s. In this period of research in the AI field it was believed that the addition of a few rules of reasoning combined with powerful computers could produce a superhuman performance expert. During this time, researchers Allen Newell and Herbert Simon developed a program called GPS (General Problem Solver). This program was able to work with cytometry, with the towers of Hanoi and similar problems. However, it was unable to fulfil its functional title, solving problems in real life.
This prompted some researchers to study the possibility of focusing their programs to a more specific domain, thus trying to simulate the way of acting and the reasoning of a human expert, which lead to the creation of Expert Systems as we know them today. One of these researchers was Edward Feigenbaum who, along with his team, managed to develop DENDRAL, the first Expert System to be used for real purposes (it was used for more than 10 years), which was a great success among chemists and biologists as it was capable of identify molecular chemical structures from their spectrographic analysis.
There are two types of Expert Systems, those based on rules and those based on probabilities.