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![Page 1: CS62S: Expert Systems Based on: The Engineering of Knowledge-based Systems: Theory and Practice A. J. Gonzalez and D. D. Dankel.](https://reader035.fdocuments.in/reader035/viewer/2022072013/56649e495503460f94b3ccfd/html5/thumbnails/1.jpg)
CS62S: Expert Systems
Based on:
The Engineering of Knowledge-based Systems: Theory and PracticeA. J. Gonzalez and D. D. Dankel
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Introduction to Knowledge-based Systems
General problem solving knowledge Intelligent program
Inference engine Knowledge base Data / Fact base
Separation of knowledge from its use
For a new problem domain – change knowledge base
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Knowledge Representation
Logic Rules Associative (semantic) networks Frames Objects
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Traditional Computer Programming
Structured sequence of steps
Algorithm
Finite amount of time
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Search – alternative to algorithmic solution
Path connecting problem to the solution
Problem space Procedurally defined Network Tree
Solution space (problem space examined)
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Search Methods
Random
Blind
Directed
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Search Types
Depth-first Breath-first Beam Hill-climbing Branch and bound Best-first A* (best-first and branch and bound)
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Heuristics vs. algorithm
Specific knowledge Rule of thumb Prior knowledge Expertise Timely solution Estimation
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Gonzalez and Dankel describes knowledge-based systems as:
“A computerized system that uses knowledge about some domain to arrive at a solution to a problem from that domain. This solution is essentially the same as that concluded by a person knowledgeable about the domain of the problem when confronted with the same problem“
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Expert systems
Separation of knowledge from how it is used
Use of highly specific domain knowledge
Heuristic rather than algorithms
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MYCIN
Used to diagnose blood disorderIncorporates all three elements
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Types of expertise
Associational
The internal workings of a system are not understood. The behaviour is used to solve problems
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Motor skills expertise
Practice makes perfect (sports, physical tasks, etc)
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Theoretical expertise
The internal workings of a device or system are well understood. The expert can solve problems never seen before.
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Advantages of Expert Systems
Wide distribution of scarce expertise Ease of modification Consistency of answers Perpetual accessibility Preservation of expertise Solution of Problem involving
incomplete data Explanation of solution
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Disadvantages
Answers may not always be correct
Knowledge limited to the domain of expertise
Lack of common sense
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Expert systems architecture
User
Knowledge engineer
Tool builder
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