A knowledge-based system (KBS) is an artificial intelligence (AI)-based one that uses information from various sources to generate new knowledge to help people make decisions. These devices have built-in problem-solving capabilities and rely extensively on data to provide accurate results.
KBSs are made up of two critical components—a knowledge base and an inference engine. The knowledge base contains all necessary data, while the inference engine tells the system how to process data. Most KBSs have user interfaces (UIs) to make it easy for users to send requests and interact with them.
Read More about the “Knowledge-Based System”
The term “knowledge-based system” encompasses all computer programs that use a knowledge base to generate reasons and solutions. It is a significant application of AI that is applied in several industries.
Now that we know what is a knowledge-based system, we understand that it is a broad term that could refer to several computer programs. Below are some types of knowledge-based systems based on the inference engines.
Types of Knowledge-Based Systems
There are five kinds of KBSs defined in greater detail below.
- Intelligent tutoring systems: These are computer systems that provide personalized instructions and feedback to users. Intelligent tutoring systems are used in education to help students learn even without a human teacher.
- Expert systems: Expert systems are among the most common types of KBSs. They mimic the decision-making process of a human expert and provide explanations specific to the problem they are designed to solve. If you’re interested to learn more about expert systems, you can check out this explanatory guide we published a while ago.
- Hypertext manipulation systems: These are computer systems that store knowledge using hypertext or text linked to others. Because of the way they store information, users of hypertext manipulation systems can easily access other data.
- Case-based systems: Case-based systems are designed to provide solutions based on past knowledge applied to a similar situation.
- Rule-based systems: These computer programs apply hardcoded man-made rules to analyze and manipulate data.
Advantages of Using Knowledge-Based Systems
Like other AI applications, a KBS can help make tasks easier to do for users. Productivity thus improves since solutions to complex problems are immediately available. Users can focus on their core functions and prevent repetitive tasks from taking the bulk of their time.
In the business-to-consumer (B2C) setting, having a KBS can speed up the delivery of goods and services. A KBS also comes in handy when experts are not immediately available. For example, in a medical laboratory setting, patients may no longer need to show the laboratory results to doctors, as a KBS can diagnose certain medical conditions.
KBSs also accelerate the rate of innovation in a particular field. An example is the medical KBS featured in the video below. The system can help medical practitioners develop new treatment plans based on learnings from past patients.
Challenges in Using Knowledge-Based Systems
Using KBSs is not without issues. Knowing the possible challenges these systems pose can help users detect and avoid errors that can cause significant problems. An error in the medical diagnosis done by a KBS, for instance, can result in incorrect medication. This mistake could cost the patient’s life and the medical facility’s reputation.
Some anomalies to look out for when using a KBS include redundant rules and circular dependencies. These could affect the system’s reasoning ability and give erroneous results.
Another challenge that KBS administrators face is the need for accurate and extensive data. The more data in a system’s knowledge base, the better the inferences the KBS makes. Needless to say, if the data the system relies on is inaccurate, its inferences would also be incorrect.
A KBS can make processes more accessible and efficient when appropriately designed and provided with accurate and complete data. It can even pave the way for more developments and innovations.