Introduction to Expert Introduction to Expert Systems Systems Dr. - - PowerPoint PPT Presentation

introduction to expert introduction to expert systems
SMART_READER_LITE
LIVE PREVIEW

Introduction to Expert Introduction to Expert Systems Systems Dr. - - PowerPoint PPT Presentation

Introduction to Expert Introduction to Expert Systems Systems Dr. Khaled Shaalan Prof. Dr. Ahmed Rafea Central Lab. For Agricultural Expert Central Lab. For Agricultural Expert Systems Systems Topics What is AI ? What is KBS?


slide-1
SLIDE 1

Introduction to Expert Introduction to Expert Systems Systems

  • Dr. Khaled Shaalan
  • Prof. Dr. Ahmed Rafea

Central Lab. For Agricultural Expert Central Lab. For Agricultural Expert Systems Systems

slide-2
SLIDE 2

Topics

  • What is AI ?
  • What is KBS?
  • What is expert system?
  • The structure of an expert system
  • Characteristics of an expert system
  • When are expert systems useful?
  • The players in the expert system game
  • Evolution of expert systems
slide-3
SLIDE 3

What is AI?

ARTIFICIAL INTELLIGENCE (AI) IS A BRANCH OF COMPUTER SCIENCE THAT IS STUDYING HOW TO LET COMPUTERS PERFORM FUNCTIONS CONSIDERED TO BE HIGH LEVEL HUMAN ACTIVITIES

slide-4
SLIDE 4

What is KBS?

A KNOWLEDGE - BASED SYSTEM (KBS) IS A COMPUTER PROGRAM THAT USES KNOWLEDGE AND PROBLEM SOLVING TECHNIQUES

slide-5
SLIDE 5

What is expert system?

AN EXPERT SYSTEM (ES) IS A COMPUTER PROGRAM DESIGNED TO SIMULATE THE PROBLEM- SOLVING BEHAVIOR OF AN EXPERT IN A NARROW DOMAIN OR DISCIPLINE.

slide-6
SLIDE 6

What is expert system?(cont.)

ARTIFICIAL INTELLIGENCE PROGRAMS Exhibit intelligent behavior by skillful application of heuristics make domain knowledge explicit and separate from the rest of the system KNOWLEDGE-BASED SYSTEMS Apply expert knowledge to difficult, real world problems EXPERT SYSTEMS

slide-7
SLIDE 7

The structure of an expert system

KNOWLEDGE BASE Domain Knowledge FACTS RULES INTERPRETER SCHEDULER

Organizing Knowledge

EXPERT SYSTEM

INFERENCE ENGINE General problem-solving knowledge

slide-8
SLIDE 8

Representing knowledge

Rule-based methods Frame-based methods

slide-9
SLIDE 9

Rules

A rule is a formal way of specifying a

recommendation, directive, or advice

A rule is expressed as

IF IF premise premise THEN THEN conclusion conclusion

  • r

IF IF condition condition THEN THEN action action

slide-10
SLIDE 10

A diagnostic rule

IF IF there are spots on leaves, and the color of spots is pale yellow, gray, or purple, and the shape of spots is bounded making acute angle with veins, and the season is spring Then Then the disease is downy mildew - probability = 0.9

slide-11
SLIDE 11

A treatment rule

IF IF the disease is downy mildew THEN THEN the treatment method is chemical spraying, and the material used is redomil+copper

slide-12
SLIDE 12

Drawing inferences from rules

Forward chaining Backward chaining

slide-13
SLIDE 13

Frames

A frame is a description of an object that

contains slots for all of the information associated with the object

Slots may contain (default) values, or

procedures by which values may be

  • btained
slide-14
SLIDE 14

Soil Frame

Slots Facets Ph value type: real single/multiple: single possible value: > 0.0 & 14.0 EC value type: real single/multiple: single possible value: > 0.0 Texture value type: nominal single/multiple: single possible value: sand, loam, clay, heavy clay, gravely, coarse sand, silty clay, silty clay loam, salt loam, fine sand, sand clay loam, silt loam, sandy loam, loamy fine sand … …

slide-15
SLIDE 15

Frames connected by IS-A relation

Leaf mold Downy mildew Fungal Mosaic Green Mosaic Viral Disease Spiders Broad mite Mites Low temperature Heavy irrigation Environmental aphids Insect Nitrogen Iron Nutrition Deficiency Bromide Bazamide Toxicity Root knot Root lesion Nematode Disorder

Disorder hierarchy

generic specialized

slide-16
SLIDE 16

Drawing inferences from frames

Inheritance Procedure attachment

slide-17
SLIDE 17

Characteristics of an expert system

Expert System Expertise Symbolic reasoning Depth Self-knowledge Exhibit expert performance Have high level of skill Have adequate robustness Represent knowledge symbolically Reformulate symbolic knowledge Handle difficult problem domains Use complex rules Examine its own reasoning Explain its operation

slide-18
SLIDE 18

When are expert systems useful?

Nature of the task

– Experts can do better than nonexperts – The task involves reasoning and knowledge, not intuitions or reflexes – The task can be done by a person in minutes or hours – The task is concrete enough to codify – The task is commonly taught to novices in the area

slide-19
SLIDE 19

When are expert systems useful?

(Cont.)

Availability of knowledge

– Recognized experts exist – There is general agreement among experts – Experts are able and willing to articulate the way they approach problems

slide-20
SLIDE 20

The players in the expert system game

Tool builder

EXPERT SYSTEM BUILDING TOOL Domain expert Knowledge engineer EXPERT SYSTEM Clerical Staff End-user Interviews Builds refines and tests Extends and test Builds Uses Uses

slide-21
SLIDE 21

Programming language Shell

Expert system building tool

slide-22
SLIDE 22

Shells VS Programming languages

Features Shells

  • Prog. Lang.

Ease & speed of development Higher Less KB Structure &reasoning Restricted by the tool May be developed As needed KB maintenance Easier Difficult

slide-23
SLIDE 23

Shells VS Programming languages (Cont.)

Features Shells

  • Prog. Lang.

Interfaces Not always friendly or available Have to be developed Efficiency/ Performance Slower Faster Explanation Restricted by the tool May be developed as needed

slide-24
SLIDE 24

Evolution of expert systems

Development Stage Description Demonstration Prototype The system solves a portion of the problem undertaken, suggesting that the approach is viable and system development is achievable. (test ideas) Research prototype The system displays credible performance on the entire problem but may be fragile due to incomplete testing and revision. (test cases) Field prototype The system displays good performance with adequate reliability and has been revised based on extensive testing in the user environment. (test real problems) Production model The system exhibits high quality, reliable, fast, and efficient performance in the user environment. (extensive field tests) Commercial system The system is a production model being used on a regular commercial basis.