1. Introduction
• Artificial intelligence: science of enabling computers to behave intelligently
• Knowledge-based system (or expert system): a program which exhibits,
within a specific domain, a degree of expertise in problem solving that is
comparable with a human expert
• expert: person with superior knowledge in some particular field, usually only
obtained through experience
• knowledge base: repository of expert's rules and facts about a domain
• inference engine: procedure for drawing conclusions from knowledge base
• knowledge engineer: develops, implements, and maintains a model of an
expert's knowledge base
• expert system shell: software used to implement an expert system;
usually generic (and commercialized)

2. Terms (cont)
• heuristics: methods of findings solutions so as to promote efficiency
- inference engine typically employs domain-specific heuristics so that
solutions can be found reasonably fast
• fact: simple assertion of a truth
eg. mother (jane, john).
• rule: a conditional or causal relationship
eg. if is_a_tiger then not(pet)
• meta-rule: a rule that describes a rule , part of a theory of knowledge
eg. if true_examples_exist(rule) and no_counter_examples(rule)
then universal_truth(rule)

3. Nature of knowledge (Hall)
"common sense"
Informal
Technical
Formal
mathematical, algorithmic
domain-specific rules

4. Knowledge (cont) • technical vs. formal: - both can be formalized
- technical: theory remain same, data changes
eg. mathematical formulae, programs
formal: rules change, ie. rules are data
• knowledge-based systems are concerned with processing formal knowledge
- can employ technical knowledge to help
• note: formalizing informal knowledge is a major focus of
AI research in machine learning

5. Structure of a KBS Knowledge Base I n "Real world" t e r ( humans, f
robots,
machines, ... )
Inference
Engine
Working
Storage

6. Expert Systems vs. conventional programs
Similarities
• both programmed in a programming language
• design processes are similar
Design Prototype Test Production
Revise
• both get "bugs"
Differences
• KBS uses knowledge base with domain rules
• KBS uses (domain-dependent) heuristics

7. (cont) • expert systems have an explanation facility
• expert systems may have a learning component
* design & implementation of KBS requires knowledge engineering,
and use of expert knowledge
- uncertain and probabilistic knowledge
- conflicting knowledge
- unknown

8. Conventional pgms vs Ex.Sys
Conventional programs Expert Systems
Numeric Symbolic
Algorithmic Heuristic
Info & control integrated Knowledge & control separated
Difficult to modify Easier to modify
Precise info Uncertain info
Command interface Natural dialog w explanation
Final result given Recommendation(s) w expl
Optimal solution Acceptable solution(s)

9. Why use expert systems?
• expertise often required in complex human activities
• expertise is expensive and rare
• level of expertise can vary widely
• experience in a field is difficult to easily obtain
• Expert systems:
- are relatively cheap
- are consistent, objective, and not prone to stress

10. Some application areas...
• finances: financial planning, stock market, tax preparation, banking, ...
• law: interpretation of legal text, legal inferences
• medicine: diagnosis and treatment
• scientific: chemistry
• engineering: machine monitoring and control
• robotics
• weather forecasting