artificial intelligence: expert systems components

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Artificial Intelligence (AI): Expert Systems Components • Definition • Subfields

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This presentation is an introduction to artificial intelligence: expert systems components. Topics covered are the following: defining artificial intelligence; expert systems key terms; expert systems requirements; expert systems components; and selecting appropriate problems for expert systems.

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Page 1: Artificial Intelligence: Expert Systems Components

Artificial Intelligence (AI):Expert Systems Components

• Definition

• Subfields

Page 2: Artificial Intelligence: Expert Systems Components

Expert Systems

• Definition

• Key Terms

• Requirements

• Components

• Selecting appropriate problems for ES

Page 3: Artificial Intelligence: Expert Systems Components

Definition of AI

• From an intelligence perspective– Artificial Intelligence is making “intelligent”

machines which perform like humans– Example: Turing Test – inability to

distinguish computer responses from human responses

Page 4: Artificial Intelligence: Expert Systems Components

Definition of AI (con’t)

• From a research perspective – The study of making computers perform

tasks which people do better– Examples

• Checker players• Learning, reasoning, etc.

• Computers are good at Deduction

• Humans are good at Induction

Page 5: Artificial Intelligence: Expert Systems Components

Definition of AI (con’t)

• From a business perspective – AI is a set of very powerful tools, and

methodologies for using those tools to solve business problems

– Example• Who is an embezzler?

– Deductive Reasoning will not determine– Only Inductive Reasoning will

Page 6: Artificial Intelligence: Expert Systems Components

Definition of AI (con’t)

• From a programming perspective– AI includes the study of symbolic

programming, problem solving, and search – Example

• LISP, PROLOG, & ML– LISP Machine: Machine Language-Assembler/C– Execute LISP application very quickly on a LISP

machine (1980’s/Not a survivor)

Page 7: Artificial Intelligence: Expert Systems Components

Comparison 1 (Advantage of AI)

• Natural Intelligence-Humans– Perishable– Difficult to transfer– Difficult to document– Unpredictable– Expensive– Not available always

• Artificial Intelligence-Machines– Institutional Memory– Easy to transfer– Easy to document– Consistent– Affordable– Available always

Page 8: Artificial Intelligence: Expert Systems Components

Comparison II (Limitations of AI)

• Natural Intelligence– Creative– Adaptive– Sensory experience– Broad Focus– Common Sense

• Artificial Intelligence– Uninspired– Needs to be told– Symbolic Input– Narrow Focus– Technical

Page 9: Artificial Intelligence: Expert Systems Components

Subfields of AI• Expert Systems

• Natural Language

• Machine Learning (Artificial Neural Network/Statistical Inferences

• Computer Vision (Image Processing)– Examples

• Automotive Automobile Driver

• Artificial Eyes

• DoD (Research side)

• Highly mathematically involved

Page 10: Artificial Intelligence: Expert Systems Components

Expert Systems

• A computer-based information system that uses expert knowledge to attain high levels of performance in a narrow problem area

Page 11: Artificial Intelligence: Expert Systems Components

Key Terms

• Expert, Domain Expert

• Knowledge-based Systems

• Intelligent Systems

• Knowledge Engineering

• Knowledge Engineer

• Domain Knowledge