Expert Systems

Overview

An expert system is a computer program that contains knowledge and expertise in a specific domain to solve complex problems. These systems use a knowledge base, inference engine, and user interface to replicate human decision-making.

"Expert systems can perform tasks that would otherwise require human expertise, such as medical diagnoses or legal advice." - Artificial Intelligence: A Modern Approach

History

1960s

Early Systems

1965 - DENDRAL system for chemical analysis
1976 - MYCIN for diagnosing bacterial infections

1980s

Commercial Interest

1982 - XCON for configuring computer systems
1985 - CLIPS system released by NASA

System Components

Knowledge Base

Stores domain-specific facts and rules, often represented as "if-then" statements for inference.

Inference Engine

Applies logical rules to the knowledge base to deduce new information or make decisions.

Development Process

Knowledge Elicitation: Extracting expertise from human experts
Knowledge Representation: Formatting the knowledge using formal notations
System Construction: Building the inference engine and user interface
Testing & Validation: Ensuring the system behaves as expected

Example Implementation

; Simple medical diagnosis rule in CLIPS
(defrule fever-check
    (patient (symptoms (member ?"fever" *)))
    =>
    (printout t "Patient may have a bacterial infection. Consider antibiotic treatment." crlf))
                

Applications

Healthcare

Used for disease diagnosis, drug interactions detection, and treatment recommendations

Finance

Applies to fraud detection, loan risk assessment, and investment strategies

Engineering

Assists with system maintenance, fault diagnosis, and design optimization

Legal

Helps with case research, legal document analysis, and compliance checking

Limitations

Difficulty encoding common sense knowledge and emergent behaviors
Can only perform as well as their knowledge base and rule sets
Complex systems may require continuous maintenance and updates