SlideShare ist ein Scribd-Unternehmen logo
1 von 32
CLIPS: Expert System Shell Motaz K. Saad College of IT – CS Dept.
What is expert system? ,[object Object]
What is expert system? 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
The structure of an expert system KNOWLEDGE BASE  Domain Knowledge  INFERENCE ENGINE  General  problem-solving  knowledge FACTS RULES INTERPRETER SCHEDULER
Facts and Rules ,[object Object],[object Object],[object Object]
Rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
Drawing inferences from rules ,[object Object],[object Object],[object Object],[object Object]
Expert system building tool ,[object Object],[object Object],[object Object],[object Object]
Shells vs. Programming languages
Shells vs. Programming languages
CLIPS: Expert System Shell ,[object Object]
The CLIPS Programming Tool ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Components of CLIPS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Defining Facts ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Managing Facts ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Defining Rules ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
An Example CLIPS Rule ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Getting the Rules Started ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tracing & Recording Things ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Variables & Pattern Matching ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Retracting Facts from a Rule ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Pattern Matching Details ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Using Templates ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Defining Functions in CLIPS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Defining Classes & Instances ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Concrete & Abstract Classes ,[object Object],Person Man Woman Jack Jill
Managing Instances ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Clearing & Resetting Instances ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Message Passing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Limitations of CLIPS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Alternatives to CLIPS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The End! http://motaz.saad.googlepages.com

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (20)

Knowledge representation In Artificial Intelligence
Knowledge representation In Artificial IntelligenceKnowledge representation In Artificial Intelligence
Knowledge representation In Artificial Intelligence
 
Lecture 17 Iterative Deepening a star algorithm
Lecture 17 Iterative Deepening a star algorithmLecture 17 Iterative Deepening a star algorithm
Lecture 17 Iterative Deepening a star algorithm
 
BackTracking Algorithm: Technique and Examples
BackTracking Algorithm: Technique and ExamplesBackTracking Algorithm: Technique and Examples
BackTracking Algorithm: Technique and Examples
 
sum of subset problem using Backtracking
sum of subset problem using Backtrackingsum of subset problem using Backtracking
sum of subset problem using Backtracking
 
Divide and conquer
Divide and conquerDivide and conquer
Divide and conquer
 
Forward Backward Chaining
Forward Backward ChainingForward Backward Chaining
Forward Backward Chaining
 
Hill climbing algorithm
Hill climbing algorithmHill climbing algorithm
Hill climbing algorithm
 
Game Playing in Artificial Intelligence
Game Playing in Artificial IntelligenceGame Playing in Artificial Intelligence
Game Playing in Artificial Intelligence
 
Knowledge representation and reasoning
Knowledge representation and reasoningKnowledge representation and reasoning
Knowledge representation and reasoning
 
Syntax directed translation
Syntax directed translationSyntax directed translation
Syntax directed translation
 
Artificial intelligence and knowledge representation
Artificial intelligence and knowledge representationArtificial intelligence and knowledge representation
Artificial intelligence and knowledge representation
 
0 1 knapsack using branch and bound
0 1 knapsack using branch and bound0 1 knapsack using branch and bound
0 1 knapsack using branch and bound
 
Semantic nets in artificial intelligence
Semantic nets in artificial intelligenceSemantic nets in artificial intelligence
Semantic nets in artificial intelligence
 
And or graph problem reduction using predicate logic
And or graph problem reduction using predicate logicAnd or graph problem reduction using predicate logic
And or graph problem reduction using predicate logic
 
Advanced data structures & algorithms important questions
Advanced data structures & algorithms important questionsAdvanced data structures & algorithms important questions
Advanced data structures & algorithms important questions
 
Rule based system
Rule based systemRule based system
Rule based system
 
Decision tree in artificial intelligence
Decision tree in artificial intelligenceDecision tree in artificial intelligence
Decision tree in artificial intelligence
 
Unification and Lifting
Unification and LiftingUnification and Lifting
Unification and Lifting
 
Chapter 1 (final)
Chapter 1 (final)Chapter 1 (final)
Chapter 1 (final)
 
Introduction to prolog
Introduction to prologIntroduction to prolog
Introduction to prolog
 

Andere mochten auch

OS Lab: Introduction to Linux
OS Lab: Introduction to LinuxOS Lab: Introduction to Linux
OS Lab: Introduction to Linux
Motaz Saad
 
Open Source Business Models
Open Source Business ModelsOpen Source Business Models
Open Source Business Models
Motaz Saad
 

Andere mochten auch (20)

Ai lecture 07 inference engine
Ai lecture 07 inference engineAi lecture 07 inference engine
Ai lecture 07 inference engine
 
Inference engine
Inference engineInference engine
Inference engine
 
The Role Of Ontology In Modern Expert Systems Dallas 2008
The Role Of Ontology In Modern Expert Systems   Dallas   2008The Role Of Ontology In Modern Expert Systems   Dallas   2008
The Role Of Ontology In Modern Expert Systems Dallas 2008
 
CLIPS Basic Student Guide
CLIPS Basic Student GuideCLIPS Basic Student Guide
CLIPS Basic Student Guide
 
Expert System - Automated Traffic Light Control Based on Road Congestion
Expert System - Automated Traffic Light Control Based on Road CongestionExpert System - Automated Traffic Light Control Based on Road Congestion
Expert System - Automated Traffic Light Control Based on Road Congestion
 
Introduction To Mycin Expert System
Introduction To Mycin Expert SystemIntroduction To Mycin Expert System
Introduction To Mycin Expert System
 
Expert system neural fuzzy system
Expert system neural fuzzy systemExpert system neural fuzzy system
Expert system neural fuzzy system
 
EXPERT SYSTEM FOR LOAN BY BANK
EXPERT SYSTEM  FOR LOAN BY BANKEXPERT SYSTEM  FOR LOAN BY BANK
EXPERT SYSTEM FOR LOAN BY BANK
 
Intel 64bit Architecture
Intel 64bit ArchitectureIntel 64bit Architecture
Intel 64bit Architecture
 
مقدمة في تكنواوجيا المعلومات
مقدمة في تكنواوجيا المعلوماتمقدمة في تكنواوجيا المعلومات
مقدمة في تكنواوجيا المعلومات
 
Hewahi, saad 2006 - class outliers mining distance-based approach
Hewahi, saad   2006 - class outliers mining distance-based approachHewahi, saad   2006 - class outliers mining distance-based approach
Hewahi, saad 2006 - class outliers mining distance-based approach
 
3.7 outlier analysis
3.7 outlier analysis3.7 outlier analysis
3.7 outlier analysis
 
Assembly Language Lecture 5
Assembly Language Lecture 5Assembly Language Lecture 5
Assembly Language Lecture 5
 
Browsing The Source Code of Linux Packages
Browsing The Source Code of Linux PackagesBrowsing The Source Code of Linux Packages
Browsing The Source Code of Linux Packages
 
Cross Language Concept Mining
Cross Language Concept Mining Cross Language Concept Mining
Cross Language Concept Mining
 
Class Outlier Mining
Class Outlier MiningClass Outlier Mining
Class Outlier Mining
 
Knowledge discovery thru data mining
Knowledge discovery thru data miningKnowledge discovery thru data mining
Knowledge discovery thru data mining
 
OS Lab: Introduction to Linux
OS Lab: Introduction to LinuxOS Lab: Introduction to Linux
OS Lab: Introduction to Linux
 
Browsing Linux Kernel Source
Browsing Linux Kernel SourceBrowsing Linux Kernel Source
Browsing Linux Kernel Source
 
Open Source Business Models
Open Source Business ModelsOpen Source Business Models
Open Source Business Models
 

Ähnlich wie Introduction to CLIPS Expert System

Threaded Programming
Threaded ProgrammingThreaded Programming
Threaded Programming
Sri Prasanna
 
Linq To The Enterprise
Linq To The EnterpriseLinq To The Enterprise
Linq To The Enterprise
Daniel Egan
 
Linq 1224887336792847 9
Linq 1224887336792847 9Linq 1224887336792847 9
Linq 1224887336792847 9
google
 
r,rstats,r language,r packages
r,rstats,r language,r packagesr,rstats,r language,r packages
r,rstats,r language,r packages
Ajay Ohri
 
Eclipse Modeling Framework
Eclipse Modeling FrameworkEclipse Modeling Framework
Eclipse Modeling Framework
Ajay K
 

Ähnlich wie Introduction to CLIPS Expert System (20)

L04 Software Design Examples
L04 Software Design ExamplesL04 Software Design Examples
L04 Software Design Examples
 
SystemVerilog OOP Ovm Features Summary
SystemVerilog OOP Ovm Features SummarySystemVerilog OOP Ovm Features Summary
SystemVerilog OOP Ovm Features Summary
 
Patterns in Python
Patterns in PythonPatterns in Python
Patterns in Python
 
Twins: Object Oriented Programming and Functional Programming
Twins: Object Oriented Programming and Functional ProgrammingTwins: Object Oriented Programming and Functional Programming
Twins: Object Oriented Programming and Functional Programming
 
Kerberizing Spark: Spark Summit East talk by Abel Rincon and Jorge Lopez-Malla
Kerberizing Spark: Spark Summit East talk by Abel Rincon and Jorge Lopez-MallaKerberizing Spark: Spark Summit East talk by Abel Rincon and Jorge Lopez-Malla
Kerberizing Spark: Spark Summit East talk by Abel Rincon and Jorge Lopez-Malla
 
ScalaDays 2013 Keynote Speech by Martin Odersky
ScalaDays 2013 Keynote Speech by Martin OderskyScalaDays 2013 Keynote Speech by Martin Odersky
ScalaDays 2013 Keynote Speech by Martin Odersky
 
A brief overview of java frameworks
A brief overview of java frameworksA brief overview of java frameworks
A brief overview of java frameworks
 
Threaded Programming
Threaded ProgrammingThreaded Programming
Threaded Programming
 
Groovy Introduction - JAX Germany - 2008
Groovy Introduction - JAX Germany - 2008Groovy Introduction - JAX Germany - 2008
Groovy Introduction - JAX Germany - 2008
 
Linq To The Enterprise
Linq To The EnterpriseLinq To The Enterprise
Linq To The Enterprise
 
Linq 1224887336792847 9
Linq 1224887336792847 9Linq 1224887336792847 9
Linq 1224887336792847 9
 
Practical catalyst
Practical catalystPractical catalyst
Practical catalyst
 
TWINS: OOP and FP - Warburton
TWINS: OOP and FP - WarburtonTWINS: OOP and FP - Warburton
TWINS: OOP and FP - Warburton
 
Clojure And Swing
Clojure And SwingClojure And Swing
Clojure And Swing
 
Devoxx
DevoxxDevoxx
Devoxx
 
r,rstats,r language,r packages
r,rstats,r language,r packagesr,rstats,r language,r packages
r,rstats,r language,r packages
 
닷넷 개발자를 위한 패턴이야기
닷넷 개발자를 위한 패턴이야기닷넷 개발자를 위한 패턴이야기
닷넷 개발자를 위한 패턴이야기
 
Eclipse Modeling Framework
Eclipse Modeling FrameworkEclipse Modeling Framework
Eclipse Modeling Framework
 
Beyond Breakpoints: A Tour of Dynamic Analysis
Beyond Breakpoints: A Tour of Dynamic AnalysisBeyond Breakpoints: A Tour of Dynamic Analysis
Beyond Breakpoints: A Tour of Dynamic Analysis
 
You Might Just be a Functional Programmer Now
You Might Just be a Functional Programmer NowYou Might Just be a Functional Programmer Now
You Might Just be a Functional Programmer Now
 

Mehr von Motaz Saad (8)

Structured Vs, Object Oriented Analysis and Design
Structured Vs, Object Oriented Analysis and DesignStructured Vs, Object Oriented Analysis and Design
Structured Vs, Object Oriented Analysis and Design
 
The x86 Family
The x86 FamilyThe x86 Family
The x86 Family
 
Assembly Language Lecture 4
Assembly Language Lecture 4Assembly Language Lecture 4
Assembly Language Lecture 4
 
Assembly Language Lecture 3
Assembly Language Lecture 3Assembly Language Lecture 3
Assembly Language Lecture 3
 
Assembly Language Lecture 2
Assembly Language Lecture 2Assembly Language Lecture 2
Assembly Language Lecture 2
 
Assembly Language Lecture 1
Assembly Language Lecture 1Assembly Language Lecture 1
Assembly Language Lecture 1
 
Introduction to Assembly Language
Introduction to Assembly LanguageIntroduction to Assembly Language
Introduction to Assembly Language
 
Data Mining and Business Intelligence Tools
Data Mining and Business Intelligence ToolsData Mining and Business Intelligence Tools
Data Mining and Business Intelligence Tools
 

Kürzlich hochgeladen

Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 

Kürzlich hochgeladen (20)

Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 

Introduction to CLIPS Expert System

  • 1. CLIPS: Expert System Shell Motaz K. Saad College of IT – CS Dept.
  • 2.
  • 3. What is expert system? 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
  • 4. The structure of an expert system KNOWLEDGE BASE Domain Knowledge INFERENCE ENGINE General problem-solving knowledge FACTS RULES INTERPRETER SCHEDULER
  • 5.
  • 6.
  • 7.
  • 8.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.