SlideShare a Scribd company logo
1 of 11
(Centrefor KnowledgeTransfer)
institute
PRODUCTION
SYSTEM
IN
ARTIFICIAL INTELLIGENCE
Dr. C.V. Suresh Babu
(Centrefor KnowledgeTransfer)
institute
Discussion
Topics
A production system is based on a set of rules about
behaviour.These rules are a basic representation found
helpful in expert systems, automated planning, and
action selection. It also provides some form of artificial
intelligence.
• What is Production System?
• Features of Production System
• Control/Search Strategies
• Production System Rules
• Classes of Production System
• Advantages & Disadvantages
• Production System in AI: Example
(Centrefor KnowledgeTransfer)
institute
What is
Production
System?
• Production system or production rule system is a
computer program typically used to provide some form
of artificial intelligence, which consists primarily of a
set of rules about behavior but it also includes the
mechanism necessary to follow those rules as the
system responds to states of the world.
(Centrefor KnowledgeTransfer)
institute
Components
of a
production
system
The major components of Production System in Artificial
Intelligence are:
• Global Database:The global database is the central
data structure used by the production system in
Artificial Intelligence.
• Set of Production Rules:The production rules operate
on the global database. Each rule usually has a
precondition that is either satisfied or not by the global
database. If the precondition is satisfied, the rule is
usually be applied.The application of the rule changes
the database.
• A Control System:The control system then chooses
which applicable rule should be applied and ceases
computation when a termination condition on the
database is satisfied. If multiple rules are to fire at the
same time, the control system resolves the conflicts.
(Centrefor KnowledgeTransfer)
institute
Control/
Search
Strategies
How would you decide which rule to apply while
searching for a solution for any problem?There are
certain requirements for a good control strategy that you
need to keep in mind, such as:
• The first requirement for a good control strategy is that
it should cause motion.
• The second requirement for a good control strategy is
that it should be systematic.
• Finally, it must be efficient in order to find a good
answer.
(Centrefor KnowledgeTransfer)
institute
Production
System
Rules
Production System rules can be classified as:
• Deductive Inference Rules
• Abductive Inference Rules
You can represent the knowledge in a production system
as a set of rules along with a control system and database.
It can be written as:
If(Condition)Then (Condition)
• The production rules are also known as condition-
action, antecedent-consequent, pattern-action,
situation-response, feedback-result pairs
(Centrefor KnowledgeTransfer)
institute
Features
of a
Production
System
• Simplicity: Each sentence in a production system has a
if-then architecture that provides simplicity in
knowledge representation.
• Modularity: In a production system code the
knowledge is available in discrete pieces, each of which
can be treated independently.
• Modifiability: This feature allows us to form
production rule in skeleton form first and then add on
according to the need of the specific application.
• Knowledge Intensive: The knowledge base of a
production system does not contain any code or
programming. It is written in pure English.The problem
of semantics is solved by their structure of
representation.
(Centrefor KnowledgeTransfer)
institute
Classes of Production System in Artificial Intelligence
There are four major classes of Production System in Artificial Intelligence:
• Monotonic Production System: It’s a production system in which the application of a rule never prevents the later
application of another rule, that could have also been applied at the time the first rule was selected.
• Partially Commutative Production System: It’s a type of production system in which the application of a sequence
of rules transforms state X into stateY, then any permutation of those rules that is allowable also transforms state x
into stateY.Theorem proving falls under the monotonic partially communicative system.
• Non-Monotonic Production Systems:These are useful for solving ignorable problems.These systems are
important from an implementation standpoint because they can be implemented without the ability to backtrack to
previous states when it is discovered that an incorrect path was followed.This production system increases
efficiency since it is not necessary to keep track of the changes made in the search process.
• Commutative Systems:These are usually useful for problems in which changes occur but can be reversed and in
which the order of operation is not critical. Production systems that are not usually not partially commutative are
useful for many problems in which irreversible changes occur, such as chemical analysis.When dealing with such
systems, the order in which operations are performed is very important and hence correct decisions must be made
at the first attempt itself.
(Centrefor KnowledgeTransfer)
institute
Advantages
of Production
System
• Provides excellent tools for structuring AI programs
advantages - production system in artificial intelligence
• The system is highly modular because individual rules can
be added, removed or modified independently
• Separation of knowledge and Control-Recognises Act
Cycle
• A natural mapping onto state-space research data or goal-
driven
• The system uses pattern directed control which is more
flexible than algorithmic control
• Provides opportunities for heuristic control of the search
• A good way to model the state-driven nature of intelligent
machines
• Quite helpful in a real-time environment and applications.
(Centrefor KnowledgeTransfer)
institute
Disadvantages • It is very difficult to analyze the flow of control within a
production system
• It describes the operations that can be performed in a
search for a solution to the problem.
• There is an absence of learning due to a rule-based
production system that does not store the result of the
problem for future use.
• The rules in the production system should not have any
type of conflict resolution as when a new rule is added
to the database it should ensure that it does not have
any conflict with any existing rule.
(Centrefor KnowledgeTransfer)
institute
Example
Problem Statement:
• We have two jugs of capacity 5l and 3l (liter), and a tap
with an endless supply of water.The objective is to
obtain 4 liters exactly in the 5-liter jug with the
minimum steps possible.
• It is possible to have other solutions as well but these
are the shortest and the 1st sequence should be
chosen as it has the minimum number of steps.
Production System:
1. Fill the 5 liter jug from tap
2. Empty the 5 liter jug
3. Fill the 3 liter jug from tap
4. Empty the 3 liter jug
5. Then, empty the 3 liter jug to 5 liter
6. Empty the 5 liter jug to 3 liter
7. Pour water from 3 liters to 5 liter
8. Pour water from 5 liters to 3 liters but do not empty
Solution:
1,8,4,6,1,8 or 3,5,3,7,2,5,3,5;
https://www.youtube.com/watch?v=-le0Np66tAw

More Related Content

What's hot

Design cycles of pattern recognition
Design cycles of pattern recognitionDesign cycles of pattern recognition
Design cycles of pattern recognitionAl Mamun
 
Convolutional Neural Networks (CNN)
Convolutional Neural Networks (CNN)Convolutional Neural Networks (CNN)
Convolutional Neural Networks (CNN)Gaurav Mittal
 
Machine learning ppt
Machine learning pptMachine learning ppt
Machine learning pptRajat Sharma
 
Artificial Bee Colony algorithm
Artificial Bee Colony algorithmArtificial Bee Colony algorithm
Artificial Bee Colony algorithmAhmed Fouad Ali
 
Machine Learning: Introduction to Neural Networks
Machine Learning: Introduction to Neural NetworksMachine Learning: Introduction to Neural Networks
Machine Learning: Introduction to Neural NetworksFrancesco Collova'
 
knowledge representation using rules
knowledge representation using rulesknowledge representation using rules
knowledge representation using rulesHarini Balamurugan
 
2- THE CHANGING NATURE OF SOFTWARE.pdf
2- THE CHANGING NATURE OF SOFTWARE.pdf2- THE CHANGING NATURE OF SOFTWARE.pdf
2- THE CHANGING NATURE OF SOFTWARE.pdfbcanawakadalcollege
 
Issues in knowledge representation
Issues in knowledge representationIssues in knowledge representation
Issues in knowledge representationSravanthi Emani
 
Time advance mehcanism
Time advance mehcanismTime advance mehcanism
Time advance mehcanismNikhil Sharma
 
Convolution Neural Network (CNN)
Convolution Neural Network (CNN)Convolution Neural Network (CNN)
Convolution Neural Network (CNN)Suraj Aavula
 
Rotor Cipher and Enigma Machine
Rotor Cipher and Enigma MachineRotor Cipher and Enigma Machine
Rotor Cipher and Enigma MachineSaurabh Kaushik
 
BTech Pattern Recognition Notes
BTech Pattern Recognition NotesBTech Pattern Recognition Notes
BTech Pattern Recognition NotesAshutosh Agrahari
 
Dynamic and Static Modeling
Dynamic and Static ModelingDynamic and Static Modeling
Dynamic and Static ModelingSaurabh Kumar
 
Adaptive Resonance Theory
Adaptive Resonance TheoryAdaptive Resonance Theory
Adaptive Resonance TheoryNaveen Kumar
 
Lecture 06 production system
Lecture 06 production systemLecture 06 production system
Lecture 06 production systemHema Kashyap
 
Interface specification
Interface specificationInterface specification
Interface specificationmaliksiddique1
 

What's hot (20)

Design cycles of pattern recognition
Design cycles of pattern recognitionDesign cycles of pattern recognition
Design cycles of pattern recognition
 
Convolutional Neural Networks (CNN)
Convolutional Neural Networks (CNN)Convolutional Neural Networks (CNN)
Convolutional Neural Networks (CNN)
 
Machine learning ppt
Machine learning pptMachine learning ppt
Machine learning ppt
 
Associative memory network
Associative memory networkAssociative memory network
Associative memory network
 
Artificial Bee Colony algorithm
Artificial Bee Colony algorithmArtificial Bee Colony algorithm
Artificial Bee Colony algorithm
 
Machine Learning: Introduction to Neural Networks
Machine Learning: Introduction to Neural NetworksMachine Learning: Introduction to Neural Networks
Machine Learning: Introduction to Neural Networks
 
Expert system
Expert systemExpert system
Expert system
 
knowledge representation using rules
knowledge representation using rulesknowledge representation using rules
knowledge representation using rules
 
2- THE CHANGING NATURE OF SOFTWARE.pdf
2- THE CHANGING NATURE OF SOFTWARE.pdf2- THE CHANGING NATURE OF SOFTWARE.pdf
2- THE CHANGING NATURE OF SOFTWARE.pdf
 
Issues in knowledge representation
Issues in knowledge representationIssues in knowledge representation
Issues in knowledge representation
 
Time advance mehcanism
Time advance mehcanismTime advance mehcanism
Time advance mehcanism
 
Convolution Neural Network (CNN)
Convolution Neural Network (CNN)Convolution Neural Network (CNN)
Convolution Neural Network (CNN)
 
Rotor Cipher and Enigma Machine
Rotor Cipher and Enigma MachineRotor Cipher and Enigma Machine
Rotor Cipher and Enigma Machine
 
BTech Pattern Recognition Notes
BTech Pattern Recognition NotesBTech Pattern Recognition Notes
BTech Pattern Recognition Notes
 
testing
testingtesting
testing
 
Dynamic and Static Modeling
Dynamic and Static ModelingDynamic and Static Modeling
Dynamic and Static Modeling
 
Machine Learning
Machine LearningMachine Learning
Machine Learning
 
Adaptive Resonance Theory
Adaptive Resonance TheoryAdaptive Resonance Theory
Adaptive Resonance Theory
 
Lecture 06 production system
Lecture 06 production systemLecture 06 production system
Lecture 06 production system
 
Interface specification
Interface specificationInterface specification
Interface specification
 

Similar to Production based system

Similar to Production based system (20)

System Simulation and Modelling with types and Event Scheduling
System Simulation and Modelling with types and Event SchedulingSystem Simulation and Modelling with types and Event Scheduling
System Simulation and Modelling with types and Event Scheduling
 
SDLC
SDLCSDLC
SDLC
 
Production System l 10.pptx
Production System l 10.pptxProduction System l 10.pptx
Production System l 10.pptx
 
Lecture 6 expert systems
Lecture 6   expert systemsLecture 6   expert systems
Lecture 6 expert systems
 
Sad1
Sad1Sad1
Sad1
 
22-REQUIREMENT.ppt
22-REQUIREMENT.ppt22-REQUIREMENT.ppt
22-REQUIREMENT.ppt
 
Unit 1 Fundamentals of Artificial Intelligence-Part II.pptx
Unit 1  Fundamentals of Artificial Intelligence-Part II.pptxUnit 1  Fundamentals of Artificial Intelligence-Part II.pptx
Unit 1 Fundamentals of Artificial Intelligence-Part II.pptx
 
Unit 2 Concepts of system bca sem 5 unix comnecpr
Unit 2 Concepts of system bca sem 5 unix comnecprUnit 2 Concepts of system bca sem 5 unix comnecpr
Unit 2 Concepts of system bca sem 5 unix comnecpr
 
System concepts- System Analysis and design
System concepts- System Analysis and designSystem concepts- System Analysis and design
System concepts- System Analysis and design
 
Management information systems
Management information systemsManagement information systems
Management information systems
 
Lesson 9 system develpment life cycle
Lesson 9 system develpment life cycleLesson 9 system develpment life cycle
Lesson 9 system develpment life cycle
 
Chapter 4.pptx
Chapter 4.pptxChapter 4.pptx
Chapter 4.pptx
 
Software Testing
Software Testing Software Testing
Software Testing
 
Rules engine.pptx
Rules engine.pptxRules engine.pptx
Rules engine.pptx
 
System Analysis And Design 2011
System Analysis And Design  2011System Analysis And Design  2011
System Analysis And Design 2011
 
SDLC
SDLCSDLC
SDLC
 
Software Development Skills and SDLC
Software Development Skills and SDLCSoftware Development Skills and SDLC
Software Development Skills and SDLC
 
SAD_SDLC.pptx
SAD_SDLC.pptxSAD_SDLC.pptx
SAD_SDLC.pptx
 
AutonomicComputing
AutonomicComputingAutonomicComputing
AutonomicComputing
 
Cibm workshop2 chapter ten
Cibm  workshop2 chapter tenCibm  workshop2 chapter ten
Cibm workshop2 chapter ten
 

More from Dr. C.V. Suresh Babu

More from Dr. C.V. Suresh Babu (20)

Data analytics with R
Data analytics with RData analytics with R
Data analytics with R
 
Association rules
Association rulesAssociation rules
Association rules
 
Clustering
ClusteringClustering
Clustering
 
Classification
ClassificationClassification
Classification
 
Blue property assumptions.
Blue property assumptions.Blue property assumptions.
Blue property assumptions.
 
Introduction to regression
Introduction to regressionIntroduction to regression
Introduction to regression
 
DART
DARTDART
DART
 
Mycin
MycinMycin
Mycin
 
Expert systems
Expert systemsExpert systems
Expert systems
 
Dempster shafer theory
Dempster shafer theoryDempster shafer theory
Dempster shafer theory
 
Bayes network
Bayes networkBayes network
Bayes network
 
Bayes' theorem
Bayes' theoremBayes' theorem
Bayes' theorem
 
Knowledge based agents
Knowledge based agentsKnowledge based agents
Knowledge based agents
 
Rule based system
Rule based systemRule based system
Rule based system
 
Formal Logic in AI
Formal Logic in AIFormal Logic in AI
Formal Logic in AI
 
Game playing in AI
Game playing in AIGame playing in AI
Game playing in AI
 
Diagnosis test of diabetics and hypertension by AI
Diagnosis test of diabetics and hypertension by AIDiagnosis test of diabetics and hypertension by AI
Diagnosis test of diabetics and hypertension by AI
 
A study on “impact of artificial intelligence in covid19 diagnosis”
A study on “impact of artificial intelligence in covid19 diagnosis”A study on “impact of artificial intelligence in covid19 diagnosis”
A study on “impact of artificial intelligence in covid19 diagnosis”
 
A study on “impact of artificial intelligence in covid19 diagnosis”
A study on “impact of artificial intelligence in covid19 diagnosis”A study on “impact of artificial intelligence in covid19 diagnosis”
A study on “impact of artificial intelligence in covid19 diagnosis”
 
A study on “the impact of data analytics in covid 19 health care system”
A study on “the impact of data analytics in covid 19 health care system”A study on “the impact of data analytics in covid 19 health care system”
A study on “the impact of data analytics in covid 19 health care system”
 

Recently uploaded

Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝soniya singh
 
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...ranjana rawat
 
Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...
Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...
Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...Dr.Costas Sachpazis
 
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Serviceranjana rawat
 
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINEMANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINESIVASHANKAR N
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxAsutosh Ranjan
 
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service NashikCollege Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service NashikCall Girls in Nagpur High Profile
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxpranjaldaimarysona
 
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxIntroduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxupamatechverse
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130Suhani Kapoor
 
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escortsranjana rawat
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVRajaP95
 
Introduction and different types of Ethernet.pptx
Introduction and different types of Ethernet.pptxIntroduction and different types of Ethernet.pptx
Introduction and different types of Ethernet.pptxupamatechverse
 
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur High Profile
 
Booking open Available Pune Call Girls Koregaon Park 6297143586 Call Hot Ind...
Booking open Available Pune Call Girls Koregaon Park  6297143586 Call Hot Ind...Booking open Available Pune Call Girls Koregaon Park  6297143586 Call Hot Ind...
Booking open Available Pune Call Girls Koregaon Park 6297143586 Call Hot Ind...Call Girls in Nagpur High Profile
 
Extrusion Processes and Their Limitations
Extrusion Processes and Their LimitationsExtrusion Processes and Their Limitations
Extrusion Processes and Their Limitations120cr0395
 

Recently uploaded (20)

Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
 
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
(SHREYA) Chakan Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Esc...
 
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINEDJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
 
Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...
Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...
Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...
 
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
 
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINEMANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptx
 
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service NashikCollege Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
 
Processing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptxProcessing & Properties of Floor and Wall Tiles.pptx
Processing & Properties of Floor and Wall Tiles.pptx
 
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
9953056974 Call Girls In South Ex, Escorts (Delhi) NCR.pdf
 
Introduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptxIntroduction to IEEE STANDARDS and its different types.pptx
Introduction to IEEE STANDARDS and its different types.pptx
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
 
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
 
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
 
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IVHARMONY IN THE NATURE AND EXISTENCE - Unit-IV
HARMONY IN THE NATURE AND EXISTENCE - Unit-IV
 
Introduction and different types of Ethernet.pptx
Introduction and different types of Ethernet.pptxIntroduction and different types of Ethernet.pptx
Introduction and different types of Ethernet.pptx
 
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCRCall Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
 
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur EscortsHigh Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
 
Booking open Available Pune Call Girls Koregaon Park 6297143586 Call Hot Ind...
Booking open Available Pune Call Girls Koregaon Park  6297143586 Call Hot Ind...Booking open Available Pune Call Girls Koregaon Park  6297143586 Call Hot Ind...
Booking open Available Pune Call Girls Koregaon Park 6297143586 Call Hot Ind...
 
Extrusion Processes and Their Limitations
Extrusion Processes and Their LimitationsExtrusion Processes and Their Limitations
Extrusion Processes and Their Limitations
 

Production based system

  • 2. (Centrefor KnowledgeTransfer) institute Discussion Topics A production system is based on a set of rules about behaviour.These rules are a basic representation found helpful in expert systems, automated planning, and action selection. It also provides some form of artificial intelligence. • What is Production System? • Features of Production System • Control/Search Strategies • Production System Rules • Classes of Production System • Advantages & Disadvantages • Production System in AI: Example
  • 3. (Centrefor KnowledgeTransfer) institute What is Production System? • Production system or production rule system is a computer program typically used to provide some form of artificial intelligence, which consists primarily of a set of rules about behavior but it also includes the mechanism necessary to follow those rules as the system responds to states of the world.
  • 4. (Centrefor KnowledgeTransfer) institute Components of a production system The major components of Production System in Artificial Intelligence are: • Global Database:The global database is the central data structure used by the production system in Artificial Intelligence. • Set of Production Rules:The production rules operate on the global database. Each rule usually has a precondition that is either satisfied or not by the global database. If the precondition is satisfied, the rule is usually be applied.The application of the rule changes the database. • A Control System:The control system then chooses which applicable rule should be applied and ceases computation when a termination condition on the database is satisfied. If multiple rules are to fire at the same time, the control system resolves the conflicts.
  • 5. (Centrefor KnowledgeTransfer) institute Control/ Search Strategies How would you decide which rule to apply while searching for a solution for any problem?There are certain requirements for a good control strategy that you need to keep in mind, such as: • The first requirement for a good control strategy is that it should cause motion. • The second requirement for a good control strategy is that it should be systematic. • Finally, it must be efficient in order to find a good answer.
  • 6. (Centrefor KnowledgeTransfer) institute Production System Rules Production System rules can be classified as: • Deductive Inference Rules • Abductive Inference Rules You can represent the knowledge in a production system as a set of rules along with a control system and database. It can be written as: If(Condition)Then (Condition) • The production rules are also known as condition- action, antecedent-consequent, pattern-action, situation-response, feedback-result pairs
  • 7. (Centrefor KnowledgeTransfer) institute Features of a Production System • Simplicity: Each sentence in a production system has a if-then architecture that provides simplicity in knowledge representation. • Modularity: In a production system code the knowledge is available in discrete pieces, each of which can be treated independently. • Modifiability: This feature allows us to form production rule in skeleton form first and then add on according to the need of the specific application. • Knowledge Intensive: The knowledge base of a production system does not contain any code or programming. It is written in pure English.The problem of semantics is solved by their structure of representation.
  • 8. (Centrefor KnowledgeTransfer) institute Classes of Production System in Artificial Intelligence There are four major classes of Production System in Artificial Intelligence: • Monotonic Production System: It’s a production system in which the application of a rule never prevents the later application of another rule, that could have also been applied at the time the first rule was selected. • Partially Commutative Production System: It’s a type of production system in which the application of a sequence of rules transforms state X into stateY, then any permutation of those rules that is allowable also transforms state x into stateY.Theorem proving falls under the monotonic partially communicative system. • Non-Monotonic Production Systems:These are useful for solving ignorable problems.These systems are important from an implementation standpoint because they can be implemented without the ability to backtrack to previous states when it is discovered that an incorrect path was followed.This production system increases efficiency since it is not necessary to keep track of the changes made in the search process. • Commutative Systems:These are usually useful for problems in which changes occur but can be reversed and in which the order of operation is not critical. Production systems that are not usually not partially commutative are useful for many problems in which irreversible changes occur, such as chemical analysis.When dealing with such systems, the order in which operations are performed is very important and hence correct decisions must be made at the first attempt itself.
  • 9. (Centrefor KnowledgeTransfer) institute Advantages of Production System • Provides excellent tools for structuring AI programs advantages - production system in artificial intelligence • The system is highly modular because individual rules can be added, removed or modified independently • Separation of knowledge and Control-Recognises Act Cycle • A natural mapping onto state-space research data or goal- driven • The system uses pattern directed control which is more flexible than algorithmic control • Provides opportunities for heuristic control of the search • A good way to model the state-driven nature of intelligent machines • Quite helpful in a real-time environment and applications.
  • 10. (Centrefor KnowledgeTransfer) institute Disadvantages • It is very difficult to analyze the flow of control within a production system • It describes the operations that can be performed in a search for a solution to the problem. • There is an absence of learning due to a rule-based production system that does not store the result of the problem for future use. • The rules in the production system should not have any type of conflict resolution as when a new rule is added to the database it should ensure that it does not have any conflict with any existing rule.
  • 11. (Centrefor KnowledgeTransfer) institute Example Problem Statement: • We have two jugs of capacity 5l and 3l (liter), and a tap with an endless supply of water.The objective is to obtain 4 liters exactly in the 5-liter jug with the minimum steps possible. • It is possible to have other solutions as well but these are the shortest and the 1st sequence should be chosen as it has the minimum number of steps. Production System: 1. Fill the 5 liter jug from tap 2. Empty the 5 liter jug 3. Fill the 3 liter jug from tap 4. Empty the 3 liter jug 5. Then, empty the 3 liter jug to 5 liter 6. Empty the 5 liter jug to 3 liter 7. Pour water from 3 liters to 5 liter 8. Pour water from 5 liters to 3 liters but do not empty Solution: 1,8,4,6,1,8 or 3,5,3,7,2,5,3,5; https://www.youtube.com/watch?v=-le0Np66tAw