Knowledge engineering

Knowledge engineering (eng. Knowledge engineering ) - the field of science of artificial intelligence, associated with the development of expert systems and knowledge bases. Examines the methods and means of extracting, presenting, structuring and using knowledge.

Definitions

Knowledge Engineering (IZ) was defined by Feigenbaum and McCordac in 1983 as:

"IZ is a section (discipline) of engineering aimed at introducing knowledge into computer systems to solve complex problems, usually requiring a rich human experience."

Currently, this also involves the creation and maintenance of such systems (Kendal, 2007). It is also closely related to software development and is used in many information studies, such as artificial intelligence studies, including databases, data collection, expert systems, decision support systems, and geographic information systems. IZ is related to mathematical logic, which is also used in various scientific disciplines, for example, in sociology where people are “experimental”, and research goals are understanding how human logic works in relation to social relations.

Examples

An example of a system based on IZ:

• Task review
• Request to databases on the task
• Entering and structuring information received (IPK model)
• Creating a database of structured information
• Testing the information received
• Making adjustments and the evolution of the system.

Being an art rather than a purely engineering task, IZ does not have much practical use. The subsection of IZ is meta-engineering knowledge, suitable for the development of AI.

Principles

Since the mid-1980s, several principles, methods, and tools have emerged in the IZ that have facilitated the process of obtaining and working with knowledge. Here are some key ones:

• There are different types of knowledge and to work with them should be used specific methods and techniques.
• There are various types of experts and experience. To work with them should be used certain methods and techniques.
• There are different ways of providing, using, understanding knowledge and working with them can help rethink and use existing knowledge in new ways.

Knowledge engineering uses knowledge structuring techniques to speed up the process of obtaining and working with knowledge.

Theories

• Translational (traditional): involves the direct transfer of human knowledge to the machine.
• Model (alternative view): involves modeling the task and its methods for solving the AI ​​system itself.
• Hybrid.