The knowledge base in an expert system is an organized collection of facts about the system's domain. It acts as the memory of the expert system, containing all the necessary information and rules to solve problems within its specific area of expertise.
Understanding the Knowledge Base
Think of an expert system as a digital consultant. To give advice, it needs a reservoir of knowledge, which is the role of the knowledge base. This knowledge is not just random data; it's structured information specifically relevant to the system's function.
Here's a breakdown:
- Organized Collection: The knowledge base isn't simply a jumbled list. It's carefully structured to allow the system to efficiently find and use the information.
- Facts: These are the basic pieces of information the system knows. For example, in a medical expert system, a fact might be that "a fever is a symptom of infection."
- Domain-Specific: The knowledge within the base is specific to the task the expert system is designed for. A system diagnosing car problems will have a very different knowledge base from one that recommends financial investments.
- Data Storage: This stored data is essential for the inference engine to draw conclusions.
How it Works with an Inference Engine
According to the reference, expert systems rely on two main components: the knowledge base and an inference engine. The inference engine is the "thinking" part of the system. It uses the facts in the knowledge base to make logical inferences, which ultimately lead to an answer. In other words, it interprets and evaluates the facts in the knowledge base in order to provide an answer, similar to the way a human expert would use knowledge to solve a problem.
Examples of Knowledge Base in Action
Let's consider some examples:
- Medical Diagnosis: The knowledge base might contain facts about symptoms, diseases, treatments, and medical conditions. This allows the expert system to diagnose illnesses based on patient symptoms.
- Example Fact: "Coughing and sore throat can indicate a cold."
- Financial Planning: The knowledge base might have information about different investments, market trends, and financial regulations. This allows it to advise on investment strategies.
- Example Fact: "High-growth stocks often carry greater risks."
- Car Repair: An expert system for vehicle repair could store information about different car parts, their functions, and common problems. This helps mechanics diagnose car issues.
- Example Fact: "A squealing noise when braking often indicates worn brake pads."
Table Summary:
| Feature | Description |
|---|---|
| Definition | Organized collection of domain-specific facts within an expert system. |
| Function | Provides the knowledge required to solve problems within the system's domain. |
| Contents | Facts, rules, and relationships relevant to the system's expertise. |
| Relationship to Inference Engine | The inference engine uses the information to draw conclusions. |
| Example | Facts about diseases and symptoms in a medical expert system. |
In essence, the knowledge base is the foundation upon which an expert system’s reasoning is built. Without a well-structured and relevant knowledge base, the system would be unable to effectively perform its expert functions.
