Expert systems can be described in three structural components.
My description is intentionally simplified. It’s also meant to be conceptual. Actual systems may have a more complex makeup, or a different architecture altogether.
The Knowledge Base
The knowledge base makes the expert system intelligent. It’s where the domain-specific expert knowledge is stored.
The knowledge is structured in production rules. In general terms, a production is a condition, followed by an action. The action defines a step in the expert system’s reasoning process.
The Inference Engine
The inference engine manipulates and interacts with the production rules to enable the expert system to reason.
The production rules are often “if…then…” statements. If one of these conditions are satisfied, then the production rule fires or executes an action. When the production rules are chained together, the firing of one rule often causes the expert system execute or put into action a subsequent rule.
Humans interact with the inference engine through the interface. This part of the system must be able to accept human inputs and product outputs.
The interface is the point where the expert system’s expert knowledge is delivered to non-expert users.