Knowledge-based systems

What are knowledge-based systems?

Knowledge-based systems, which are also often abbreviated to WBS, represent the generic term for intelligent information systems that use knowledge with methods such as knowledge representation and / or the Knowledge modelling Evaluate and make usable. They are considered a subfield of AI research. They are always used where there are tasks that require human intelligence.

In order to solve problems, such systems use both factual knowledge as well as knowledge components with uncertainties, which are often also referred to as subjective knowledge. Knowledge-based systems also include expert systems, software agents and rule-based systems.

How are they structured?

Knowledge-based systems consist of various core components that form a complex structure here. The Knowledge base forms the basis here. Facts, rules, case-specific knowledge and generic knowledge are stored under this component. In simple terms, this area could also be called a knowledge base.

The second key point is the inference component. In this section, the various pieces of information, i.e. knowledge, are processed and new rules as well as facts are derived. The inference component is therefore the workspace in knowledge-based systems. The user interface is the last important component. This is used for general communication with the user.

Is it a complex application, two further components are addedwhich can be considered as a minor component. Often these minor components are found for expert systemsto give an example of its application.

The Knowledge component is the first new component in this extended form. This offers the possibility of expanding the knowledge base both manually and automatically. The knowledge component establishes a direct connection between the user interface and the knowledge base. This way, the knowledge base can be constantly supplied with new or changed information.

As second component is the explanatory component. Through these, information about the solution finding is communicated to the user so that it can be better understood. In short, the answers to the user's questions of how and why are given or transmitted here.

What are examples of use in practice?

Knowledge-based systems can be used very flexibly and are thus used in monitoring, in general planning, but also in data interpretation. A typical example for the use of knowledge-based systems is also medical informatics. Here, these systems are used to develop a solution to a problem with the help of patient data. In this way, a diagnosis and a possible form of therapy can be derived, which is then applied to the patient.

How are knowledge-based systems used in artificial intelligence?

Knowledge-based systems are programmes that in the Artificial intelligence as a scientific discipline are listed. These programmes use application-specific knowledge to develop different approaches to solutions. In doing so, they act completely independently and separately from the rest of the system.

However, the task of such systems is not only to provide a Processing of the specific data but also to carry out a Elimination of the often poorly structured knowledge areas to be achieved. For this purpose, a systematic stocktaking is carried out, which builds up a new structure with the help of the available expertise. In this way, gaps in knowledge can be identified and, if necessary, closed.

This new structure can then be used to develop new theories and models. Through this principle, solution paths can be created for the respective tasks that could not have been created purely based on the expertise provided at the beginning. In AI research, such systems are thus not only to be seen as a possible aid for solving problems, but also offer entirely new technical possibilities due to their structure. The computational abilities are combined here with human ways of thinking, which leads to completely new possibilities and approaches to solutions.

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