Rule-based systems
Description
Rule-based systems are a type of artificial intelligence that applies specific rules to data to derive conclusions. These systems use a collection of if-then statements (rules) and a set of known facts.
A rule-based system typically consists of:
Knowledge Base: Contains facts and rules.
Inference Engine: Applies rules to the known facts to deduce new facts.
Working Memory: Stores the current state of facts.
They are widely used in expert systems, where human knowledge is encoded as rules.
Examples (Code)
Below is a simple example
# Simple rule-based system in Python
facts = {
"temperature": "high",
"humidity": "high"
}
def apply_rules(facts):
if facts["temperature"] == "high" and facts["humidity"] == "high":
return "Turn on air conditioning"
else:
return "System normal"
print(apply_rules(facts))
# Output: Turn on air conditioning
Real-World Applications
Medical Diagnosis
Used in expert systems to suggest diagnoses based on symptoms (e.g., MYCIN).
Industrial Automation
Rules are used to automate machine behavior under various conditions.
Cybersecurity
Intrusion detection systems use rules to detect anomalies and threats.
Legal Expert Systems
Assist in interpreting and applying legal rules to case facts.
Customer Support
Chatbots use rule-based responses for common queries.
Where the Topic Is Applied
| Domain | Application |
|---|---|
| Healthcare | Diagnosis suggestion using expert systems |
| IT Security | Firewall rules and threat detection |
| Manufacturing | Control logic in automated systems |
| Finance | Fraud detection and loan eligibility rules |
| Customer Service | Automated FAQs and support responses |
Resources
Additional resources
Interview Questions with Answers
What is a rule-based system?
A rule-based system uses rules to derive conclusions from known facts using an inference engine.
What components make up a rule-based system?
It consists of a knowledge base, inference engine, and working memory.
What is forward chaining in a rule-based system?
Forward chaining starts with known facts and applies rules to infer new facts until a goal is reached.
What is backward chaining?
Backward chaining starts with a goal and works backward to determine which facts support it.
Give an example of a rule-based system in real life.
MYCIN, an early medical expert system, used rules to diagnose bacterial infections and recommend antibiotics.