Architecture (inference engine, knowledge base)
Description
The architecture of a Rule-Based System (RBS) revolves around two main components:
- the Knowledge Base and the Inference Engine. These components work together to simulate decision-making similar to that of a human expert.
- Knowledge Base: Stores a collection of facts and rules. The rules are written in the form of “IF condition THEN action.”
- Inference Engine: Applies the rules to known facts to infer new facts or reach decisions. It uses reasoning techniques such as forward chaining and backward chaining.
Examples (Code)
Below is a simple example
# Simulating a simple rule-based system
knowledge_base = {
"rules": [
{"if": {"temperature": "high"}, "then": "Turn on AC"},
{"if": {"temperature": "low"}, "then": "Turn on Heater"}
],
"facts": {"temperature": "high"}
}
def inference_engine(kb):
for rule in kb["rules"]:
if rule["if"] == kb["facts"]:
return rule["then"]
return "No action"
action = inference_engine(knowledge_base)
print(action) # Output: Turn on AC
Real-World Applications
Healthcare Diagnosis
Expert systems analyze patient symptoms using rules stored in the knowledge base.
Network Management
Inference engines apply security rules to detect and respond to threats.
Automotive Systems
Used in diagnostics and decision-making in autonomous vehicles.
Legal Advisory
Applies legal rules to client scenarios to offer preliminary advice.
Personal Assistants
Virtual assistants follow programmed rules to respond to user inputs.
Where the Topic Is Applied
| Domain | Application |
|---|---|
| Healthcare | Rule-based diagnosis systems (e.g., MYCIN) |
| Cybersecurity | Intrusion detection systems with logic-based rules |
| Finance | Loan and credit approval systems based on eligibility rules |
| Automobile | Decision support in driver assistance and self-driving systems |
| Customer Support | Chatbots using rule-based responses |
Resources
Additional resources
Interview Questions with Answers
What is the knowledge base in a rule-based system?
It is a collection of rules and facts used to derive decisions or conclusions in a rule-based system.
What role does the inference engine play?
The inference engine applies logical rules to the knowledge base to derive new facts or make decisions.
How does forward chaining work in an inference engine?
Forward chaining starts from known facts and applies rules to infer new facts until a goal is reached.
What is backward chaining?
Backward chaining begins with a goal and works backward to determine if known facts support that goal.
What is the difference between a knowledge base and a database?
A database stores raw data, while a knowledge base contains logical rules and facts designed for reasoning and decision-making.