1. EXPERT SYSTEMS
GROUP F

2. EXPERT SYSTEMS Overview What are Expert Systems?
Object-Based Knowledge (Rhonda Riggins)
Frame-Based Knowledge (JoAnna Kim)
Rule-Based Knowledge (Abbie Hoffman)
Case-Based Reasoning (Mary Mabie)
Advantages/Disadvantages (Dan Andrzejewski)

3. What Are Expert Systems?
Def: Knowledge-based info. system that uses its knowledge about a specific, complex application area to act as an expert consultant to end users
Components:
Knowledge Base
1) Information
2) Reasoning Procedures
Software Resources
1) Inference Engine

4. Object-Based Knowledge
EXPERT SYSTEMS
Object-Based Knowledge

5. Object-Based Knowledge
EXPERT SYSTEMS
Object-Based Knowledge
Definition:
“Knowledge represented as a network of objects”
Comprised of:
Object
Attribute
Value
Skin
Smooth
Texture
Rough

6. Object-Based Knowledge
EXPERT SYSTEMS
Object-Based Knowledge
Normal
High
Temperature
Smooth
Low
Texture
SKIN CONDITION
Clammy
Pale
Generalized
Rough
Color
Measles
Chicken Pox
Patchy
Reddish

7. Object-Based Knowledge
EXPERT SYSTEMS
Object-Based Knowledge
Application Category:
Design/configuration- Systems that help configure equipment components, given existing constraints.
Selection/classification- Systems that help users choose products or processes, often from among large or complex sets of alternatives.

8. Frame-Based Knowledge
EXPERT SYSTEMS
Frame-Based Knowledge

9. Frame-Based Knowledge
EXPERT SYSTEMS
Frame-Based Knowledge
represents knowledge in a hierarchical structure or a network of frames.
A frame describes all the knowledge about one particular object or concept.
Composed of:
Slots- set of attributes or characteristics that describe the object represented by the frame
Facets (or subslots)- describe some knowledge or procedure about the attribute in the slot.

10. Frame-Based Knowledge
EXPERT SYSTEMS
Frame-Based Knowledge
Physical Condition Frame
Heart Condition Frame
Skin Condition Frame
Texture Condition Frame
SLOT Temperature
-High
Facet Low Celsius
-Normal
SLOT Texture
-Rough general, patchy
-Smooth
Range
Values
Facet

11. Frame-Based Knowledge
EXPERT SYSTEMS
Frame-Based Knowledge
Application Category: Selection/Classification
Frames also allow users to choose processes from among large or complex sets of alternatives
Material selection
Delinquent account identification
Information classification

12. EXPERT SYSTEMS
Rule-Based Knowledge

13. EXPERT SYSTEMS Rule-Based Knowledge
Bases decisions on rules and facts typically represented in the form of IF/THEN statements.
These rules are a type of knowledge known as heuristics or "rules of thumb" that experts would use in their day-to-day work.
By combining the applicable rules, the expert system reaches a conclusion or makes a diagnosis.

14. EXPERT SYSTEMS Rule-Based Knowledge Example:
IF the following conditions are true:
<Pulse Oximetry is > 92%> and
<Respiratory Rate > 12> and
<FIO2 < 28%>
THEN consider the following:
<CPAP Trial for 1 Hour at 21% FIO2>
<Failure to Wean>

15. EXPERT SYSTEMS Rule-Based Knowledge
Application Category: Decision Management Systems that appraise situations or consider alternatives and make recommendations based on criteria supplied during the discovery process.
Criteria Supplied: fraction of inspired oxygen, airway passages, respiratory rate, heart rate, blood pressure, body temperature, etc.
Recommendation: Mechanical Ventilation Weaning Strategy

16. EXPERT SYSTEMS
Case-Based Reasoning

17. EXPERT SYSTEMS Case-Based Reasoning Definition:
Representing knowledge in an expert system’s knowledge base in the form of cases, i.e., examples of past performance, occurrences, and experiences (textbook, p. 487)

18. EXPERT SYSTEMS Case-Based Reasoning Case base - set of cases
Index library - search & retrieve most similar cases
Similarity metrics - measures how similar current problem to past cases
Adaptation module - creates solution
modifies the solution (structural adaptation)
creates new solution (derivational adaptation)
(Carol Brown & Daniel O’Leary, 2000, Introduction to Artificial Intelligence and Expert Systems, IV-3,

19. EXPERT SYSTEMS Case-Based Reasoning Application Category:
Decision Management
systems that appraise situation or consider alternatives and make recommendations based on criteria supplied during discovery process
Diagnostic/troubleshooting
Systems that infer underlying causes from reported symptoms and history

20. Advantages vs Human Experts
EXPERT SYSTEMS
Advantages vs Human Experts
Permanent Information
Consistent Recommendations
Easily Reproducible
Efficient Operation/Development
Complete Information
Timeliness
Other Advantages

21. Disadvantages vs Human Experts
EXPERT SYSTEMS
Disadvantages vs Human Experts
Lack of Common Sense
Lack of Creativity
Manually Updated Learning
Sensory Experience
Problem Recognition

22. EXPERT SYSTEMS
ANY QUESTIONS?