Study and Analysis of MYCIN expert system
Ankur Kumar Meena · International Journal Of Engineering And Computer Science · 2015
MYCIN was the one of the initial expert systems to perform with the level of expertise of a human expert and to provide users with complete explanation of its logical reasoning. MYCIN played a benchmark of most of the expert systems which were developed after MYCIN. Moreover, the techniques which were developed for MYCIN expert system have become most widely available design in the various small expert system building tools. It was designed to aid doctors in proper diagnosis and treatment of bacteremia infections. MYCIN was strictly a research system. The present paper provides summary of rule application concepts of MYCIN expert system. Introduction MYCIN is an expert system. By that we mean that it is an AI program designed (a) to provide expert level solutions to complex problems, (b) to be understandable, and (c) to be flexible enough to accommodate new knowledge easily. Because we have designed MYCIN to provide advice through a consultative dialogue, we sometimes refer to it as a consultation system[10][11]. There are two main parts to an expert system like MYCIN: a knowledge base and an inference mechanism, or engine (Figure 1-1). In addition there are often subprograms designed to facilitate interaction with users, to help build a knowledge base, to explain a line of reasoning, and so forth. Figure 1.1 Major Parts of an expert system. Arrows indicate information flow. The knowledge base is the program's store of facts and associations it knows about a subject area such as medicine. A critical design decision is how such knowledge is to be represented within the program. There are many choices, in general. For MYCIN, we chose to represent knowledge mostly as conditional statements, or rules, of the following form: IF: There is evidence that A and B are true, THEN: Conclude there is evidence that C is true. This form is often abbreviated to one of the following: