Expert Systems, Qualitative Reasoning, and Artificial Intelligence


Expert systems and qualitative reasoning are both branches of artificial intelligence dealing with problem solving and decision making. Expert systems emulate the decision making of humans by using a fixed inference engine, a computer program that produces reasoning based on rules and logic, to draw upon a knowledge base that can be made up of either structured or unstructured data. Qualitative reasoning automates decision making by using qualitative rather than quantitative information to improve planning and problem solving.

For each of these types of technology, the basic goal is to solve a problem that could be done by human reasoning, but either the person has incomplete knowledge of the field, or the problem involves variables that may not be immediately obvious. Both require a detailed understanding of linguistics, computer coding, and the field which the person is looking at to be successfully created. Expert systems and qualitative reasoning are used in accounting, process control, production, and rapid prototyping.

Business Value

Expert systems and qualitative reasoning require a strong understanding of usage requirements to produce value. Much of the disadvantages people consider part of these systems deal with poor development methodology. Iknow corrects this problem by creating thorough design documentation, developing an expert-level knowledge base, and gathering all requirements necessary to build internal rules and logic. When these pieces are combined, the technology becomes much more reliable, responsive and useful. These processes improve speed and accuracy in decision making by increasing the breadth of knowledge available to managers and executives.

Iknow has deep expertise in all aspects of expert systems and qualitative reasoning projects, from initial requirements gathering, to development of logic rules, to gathering data from experts in the field, to software customization and deployment. For both of these systems, they function best when integrated into an environment where standardization is one of the most important aspects, such as mortgages. They also can be used in more advanced manners to build and design prototypes of software.

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