SlideShare a Scribd company logo
1 of 12
Introduction of Predicate Logics
Prof. Neeraj Bhargava
Kapil Chauhan
Department of Computer Science
School of Engineering & Systems Sciences
MDS University, Ajmer
Outline
 Intro of Predicate logic
 Connectives
 Quantifiers
 Syntax of PL
 Semantics of PL
 Some useful equivalences
Predicate Symbols and Signatures
 Predicate symbols represent relations between zero or more
objects
 The number of objects define a predicate‘s aritiy
 Examples:
 Likes(george, kate)
 Likes(x,x)
 Likes(joe, kate, susy)
 Friends (father_of(david), father_of(andrew))
 Signature: A signature is a collection of constants, function
symbols and predicate symbols with specified arities
Connectives
 FOL formulas are joined together by logical operators to
form more complex formulas (just like in propositional
logic)
 The basic logical operators are the same as in propositional
logic as well:
 Negation: ¬p („it is not the case that p“)
 Conjunction: p ∧ q („p and q“)
 Disjunction: p ∨ q („p or q“)
 Implication: p → q („p implies q“ or “q if p“)
 Equivalence: p ↔ q („p if and only if q“)
Quantifiers
 Two quantifiers: Universal (∀) and Existential (∃)
 Allow us to express properties of collections of objects instead of
enumerating objects by name
 Apply to sentence containing variable
 Universal ∀: true for all substitutions for the variable
 “for all”: ∀<variables> <sentence>
 Existential ∃: true for at least one substitution for the variable
 “there exists”: ∃<variables> <sentence>
 Examples:
 ∃ x: Mother(art) = x
 ∀ x ∀ y: Mother(x) = Mother(y) → Sibling(x,y)
 ∃ y ∃ x: Mother(y) = x
Predicate logic, syntax
 The syntax in Luger is inspired by Prolog
 Propositions are replaced by –
 Predicate symbols (with arity) (p, q, r, …)
 – Terms, made of
 Constants (a, b, c, …)
 Variables (x, y, z, …)
 Function symbols (with arity) (f, g, h, …)
 Quantifiers ∀ (for all) and ∃ (exists)
 If ϕ is a sentence and x a variable, then ∀x:ϕ and ∃x:ϕ
are sentences.
Predicate logic, semantics
 Interpret terms as elements of a domain D.
 Interpretation I:
 • Constant: element of D.
 • Function symbol with arity n: D n → D.
 Valuation v:
 Variable: element of D.
 Interpret predicate symbols with arity n as subsets of Dn
Example: I(parent) = {(x,y) | x is the parent of y}.
Predicate logic, semantics
 If ϕ is a sentence, then
¬ϕ is T under I,v iff ϕ is F under I,v
...
∀x:ϕ is T under I,v iff ϕ is T under I,v’,
for all valuations v’ that differ from v only at x
∃x:ϕ is T under I,v iff ϕ is T under I,v’,
for some valuation v’ that differs from v only at x
Some useful equivalence
 Elimination: ∃x:p(x) ≡ ¬∀x:¬p(x)
also: ¬∃x:p(x) ≡ ∀x:¬p(x), ¬∀x:p(x) ≡ ∃x:¬p(x),
• • Names of variables can be changed:
∃x:p(x) ≡ ∃y:p(y), ∀x:p(x) ≡ ∀y:p(y)
• • ∀x:(p(x) ∧ q(x)) ≡ ∀x:p(x) ∧ ∀x:q(x) - not for ∨!
• • ∃x:(p(x) ∨ q(x)) ≡ ∃x:p(x) ∨ ∃x:q(x) - not for ∧!
Formulas
 The set of formulas is inductively defined by the following rules:
1. Preciate symbols: If P is an n-ary predicate symbol and t1,…,tn are terms then
P(t1,…,tn) is a formula.
2. Negation: If φ is a formula, then ¬φ is a formula
3. Binary connectives: If φ and ψ are formulas, then (φ → ψ) is a formula. Same for
other binary logical connectives.
4. Quantifiers: If φ is a formula and x is a variable, then ∀xφ and ∃xφ are formulas.
 Atomic formulas are formulas obtained only using the first rule
 Example: If f is a unary function symbol, P a unary predicate symbol,
and Q a ternary predicate symbol, then the following is a formula:
∀x∀y(P(f(x)) → ¬(P(x)) → Q(f(y), x, x)))
Formulas
 Any occurrence of a variable in a formulate not in the
scope of a quantifier is said to be a free occurrence
 Otherwise it is called a bound occurrence
 Thus, if x is a free variable in φ, it is bound in ∀xφ and
∃xφ
 A formula with no free variables is called a closed
formula
 Example: x and y are bound variables, z is a free
variable
∀x∀y(P(f(x)) → ¬(P(x)) → Q(f(y), x, z)))
Assignment
 Describe the predicate logic in logic of AI and discuss
the useful formulas to design facts.

More Related Content

What's hot

Predicate Logic
Predicate LogicPredicate Logic
Predicate Logicgiki67
 
Regular Languages
Regular LanguagesRegular Languages
Regular Languagesparmeet834
 
Du Calcul des prédicats vers Prolog
Du Calcul des prédicats vers PrologDu Calcul des prédicats vers Prolog
Du Calcul des prédicats vers PrologSerge Garlatti
 
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...Ashish Duggal
 
Non Standard Logics & Modal Logics
Non Standard Logics & Modal LogicsNon Standard Logics & Modal Logics
Non Standard Logics & Modal LogicsSerge Garlatti
 
Reduction Monads and Their Signatures
Reduction Monads and Their SignaturesReduction Monads and Their Signatures
Reduction Monads and Their SignaturesMarco Maggesi
 
Inductive definitions
Inductive definitionsInductive definitions
Inductive definitionslorcap
 

What's hot (14)

Chaps 1-3-ai-prolog
Chaps 1-3-ai-prologChaps 1-3-ai-prolog
Chaps 1-3-ai-prolog
 
Semantics
SemanticsSemantics
Semantics
 
Theory of computation Lec1
Theory of computation Lec1Theory of computation Lec1
Theory of computation Lec1
 
Predicate Logic
Predicate LogicPredicate Logic
Predicate Logic
 
Regular Languages
Regular LanguagesRegular Languages
Regular Languages
 
Predicate Calculus
Predicate CalculusPredicate Calculus
Predicate Calculus
 
Du Calcul des prédicats vers Prolog
Du Calcul des prédicats vers PrologDu Calcul des prédicats vers Prolog
Du Calcul des prédicats vers Prolog
 
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...
Artificial Intelligence (AI) | Prepositional logic (PL)and first order predic...
 
Non Standard Logics & Modal Logics
Non Standard Logics & Modal LogicsNon Standard Logics & Modal Logics
Non Standard Logics & Modal Logics
 
Modal Logic
Modal LogicModal Logic
Modal Logic
 
Reduction Monads and Their Signatures
Reduction Monads and Their SignaturesReduction Monads and Their Signatures
Reduction Monads and Their Signatures
 
Theory of computing
Theory of computingTheory of computing
Theory of computing
 
First order logic
First order logicFirst order logic
First order logic
 
Inductive definitions
Inductive definitionsInductive definitions
Inductive definitions
 

Similar to Introduction of predicate logics

Abdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfn
AbdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfnAbdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfn
AbdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfnNipunMeena
 
Predicate logic_2(Artificial Intelligence)
Predicate logic_2(Artificial Intelligence)Predicate logic_2(Artificial Intelligence)
Predicate logic_2(Artificial Intelligence)SHUBHAM KUMAR GUPTA
 
Chapter 01 - p2.pdf
Chapter 01 - p2.pdfChapter 01 - p2.pdf
Chapter 01 - p2.pdfsmarwaneid
 
The Chase in Database Theory
The Chase in Database TheoryThe Chase in Database Theory
The Chase in Database TheoryJan Hidders
 
GDSC SSN - solution Challenge : Fundamentals of Decision Making
GDSC SSN - solution Challenge : Fundamentals of Decision MakingGDSC SSN - solution Challenge : Fundamentals of Decision Making
GDSC SSN - solution Challenge : Fundamentals of Decision MakingGDSCSSN
 
I am kind of confused about quantifiers. I am not sure how to transl.pdf
I am kind of confused about quantifiers. I am not sure how to transl.pdfI am kind of confused about quantifiers. I am not sure how to transl.pdf
I am kind of confused about quantifiers. I am not sure how to transl.pdfAMITPANCHAL154
 
Discrete Structure Lecture #5 & 6.pdf
Discrete Structure Lecture #5 & 6.pdfDiscrete Structure Lecture #5 & 6.pdf
Discrete Structure Lecture #5 & 6.pdfMuhammadUmerIhtisham
 
FOLBUKCFAIZ.pptx
FOLBUKCFAIZ.pptxFOLBUKCFAIZ.pptx
FOLBUKCFAIZ.pptxFaiz Zeya
 
logicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdflogicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdfPradeeshSAI
 
Basic Knowledge Representation in First Order Logic.ppt
Basic Knowledge Representation in First Order Logic.pptBasic Knowledge Representation in First Order Logic.ppt
Basic Knowledge Representation in First Order Logic.pptAshfaqAhmed693399
 
Computational logic First Order Logic_part2
Computational logic First Order Logic_part2Computational logic First Order Logic_part2
Computational logic First Order Logic_part2banujahir1
 
Factoring polynomials
Factoring polynomials Factoring polynomials
Factoring polynomials eixarc
 
L03 ai - knowledge representation using logic
L03 ai - knowledge representation using logicL03 ai - knowledge representation using logic
L03 ai - knowledge representation using logicManjula V
 

Similar to Introduction of predicate logics (20)

Abdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfn
AbdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfnAbdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfn
Abdbfhdkmdmdjfmfkmfmfmfjjfjfjfnfnnfnfnfn
 
AI-09 Logic in AI
AI-09 Logic in AIAI-09 Logic in AI
AI-09 Logic in AI
 
Predicate Logic
Predicate LogicPredicate Logic
Predicate Logic
 
Predicate logic_2(Artificial Intelligence)
Predicate logic_2(Artificial Intelligence)Predicate logic_2(Artificial Intelligence)
Predicate logic_2(Artificial Intelligence)
 
Chapter 01 - p2.pdf
Chapter 01 - p2.pdfChapter 01 - p2.pdf
Chapter 01 - p2.pdf
 
The Chase in Database Theory
The Chase in Database TheoryThe Chase in Database Theory
The Chase in Database Theory
 
GDSC SSN - solution Challenge : Fundamentals of Decision Making
GDSC SSN - solution Challenge : Fundamentals of Decision MakingGDSC SSN - solution Challenge : Fundamentals of Decision Making
GDSC SSN - solution Challenge : Fundamentals of Decision Making
 
Per3 logika&amp;pembuktian
Per3 logika&amp;pembuktianPer3 logika&amp;pembuktian
Per3 logika&amp;pembuktian
 
I am kind of confused about quantifiers. I am not sure how to transl.pdf
I am kind of confused about quantifiers. I am not sure how to transl.pdfI am kind of confused about quantifiers. I am not sure how to transl.pdf
I am kind of confused about quantifiers. I am not sure how to transl.pdf
 
Polynomials
PolynomialsPolynomials
Polynomials
 
Module_5_1.pptx
Module_5_1.pptxModule_5_1.pptx
Module_5_1.pptx
 
Discrete Structure Lecture #5 & 6.pdf
Discrete Structure Lecture #5 & 6.pdfDiscrete Structure Lecture #5 & 6.pdf
Discrete Structure Lecture #5 & 6.pdf
 
Predicates
PredicatesPredicates
Predicates
 
FOLBUKCFAIZ.pptx
FOLBUKCFAIZ.pptxFOLBUKCFAIZ.pptx
FOLBUKCFAIZ.pptx
 
logicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdflogicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdf
 
1. Logic and Proofs.ppt
1. Logic and Proofs.ppt1. Logic and Proofs.ppt
1. Logic and Proofs.ppt
 
Basic Knowledge Representation in First Order Logic.ppt
Basic Knowledge Representation in First Order Logic.pptBasic Knowledge Representation in First Order Logic.ppt
Basic Knowledge Representation in First Order Logic.ppt
 
Computational logic First Order Logic_part2
Computational logic First Order Logic_part2Computational logic First Order Logic_part2
Computational logic First Order Logic_part2
 
Factoring polynomials
Factoring polynomials Factoring polynomials
Factoring polynomials
 
L03 ai - knowledge representation using logic
L03 ai - knowledge representation using logicL03 ai - knowledge representation using logic
L03 ai - knowledge representation using logic
 

More from chauhankapil

Gray level transformation
Gray level transformationGray level transformation
Gray level transformationchauhankapil
 
Elements of visual perception
Elements of visual perceptionElements of visual perception
Elements of visual perceptionchauhankapil
 
JSP Client Request
JSP Client RequestJSP Client Request
JSP Client Requestchauhankapil
 
Jsp server response
Jsp   server responseJsp   server response
Jsp server responsechauhankapil
 
Markov decision process
Markov decision processMarkov decision process
Markov decision processchauhankapil
 
RNN basics in deep learning
RNN basics in deep learningRNN basics in deep learning
RNN basics in deep learningchauhankapil
 
Introduction to generative adversarial networks (GANs)
Introduction to generative adversarial networks (GANs)Introduction to generative adversarial networks (GANs)
Introduction to generative adversarial networks (GANs)chauhankapil
 
Bayesian probabilistic interference
Bayesian probabilistic interferenceBayesian probabilistic interference
Bayesian probabilistic interferencechauhankapil
 
Exception handling in java
Exception handling in javaException handling in java
Exception handling in javachauhankapil
 
Knowledge acquistion
Knowledge acquistionKnowledge acquistion
Knowledge acquistionchauhankapil
 
Knowledge based system
Knowledge based systemKnowledge based system
Knowledge based systemchauhankapil
 
Types of inheritance in java
Types of inheritance in javaTypes of inheritance in java
Types of inheritance in javachauhankapil
 
Representation of syntax, semantics and Predicate logics
Representation of syntax, semantics and Predicate logicsRepresentation of syntax, semantics and Predicate logics
Representation of syntax, semantics and Predicate logicschauhankapil
 
Inheritance in java
Inheritance in javaInheritance in java
Inheritance in javachauhankapil
 
Propositional logic
Propositional logicPropositional logic
Propositional logicchauhankapil
 
Constructors in java
Constructors in javaConstructors in java
Constructors in javachauhankapil
 
Circular linked list
Circular linked listCircular linked list
Circular linked listchauhankapil
 
Doubly linked list
Doubly linked listDoubly linked list
Doubly linked listchauhankapil
 

More from chauhankapil (20)

Gray level transformation
Gray level transformationGray level transformation
Gray level transformation
 
Elements of visual perception
Elements of visual perceptionElements of visual perception
Elements of visual perception
 
JSP Client Request
JSP Client RequestJSP Client Request
JSP Client Request
 
Jsp server response
Jsp   server responseJsp   server response
Jsp server response
 
Markov decision process
Markov decision processMarkov decision process
Markov decision process
 
RNN basics in deep learning
RNN basics in deep learningRNN basics in deep learning
RNN basics in deep learning
 
Introduction to generative adversarial networks (GANs)
Introduction to generative adversarial networks (GANs)Introduction to generative adversarial networks (GANs)
Introduction to generative adversarial networks (GANs)
 
Bayesian probabilistic interference
Bayesian probabilistic interferenceBayesian probabilistic interference
Bayesian probabilistic interference
 
Jsp
JspJsp
Jsp
 
Exception handling in java
Exception handling in javaException handling in java
Exception handling in java
 
Knowledge acquistion
Knowledge acquistionKnowledge acquistion
Knowledge acquistion
 
Knowledge based system
Knowledge based systemKnowledge based system
Knowledge based system
 
Types of inheritance in java
Types of inheritance in javaTypes of inheritance in java
Types of inheritance in java
 
Representation of syntax, semantics and Predicate logics
Representation of syntax, semantics and Predicate logicsRepresentation of syntax, semantics and Predicate logics
Representation of syntax, semantics and Predicate logics
 
Inheritance in java
Inheritance in javaInheritance in java
Inheritance in java
 
Propositional logic
Propositional logicPropositional logic
Propositional logic
 
Constructors in java
Constructors in javaConstructors in java
Constructors in java
 
Methods in java
Methods in javaMethods in java
Methods in java
 
Circular linked list
Circular linked listCircular linked list
Circular linked list
 
Doubly linked list
Doubly linked listDoubly linked list
Doubly linked list
 

Recently uploaded

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
 
Biology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptxBiology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptxDeepakSakkari2
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxwendy cai
 
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )Tsuyoshi Horigome
 
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130Suhani Kapoor
 
main PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfidmain PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfidNikhilNagaraju
 
Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineeringmalavadedarshan25
 
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
 
Heart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptxHeart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptxPoojaBan
 
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...ranjana rawat
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxpurnimasatapathy1234
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2RajaP95
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.eptoze12
 
Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...VICTOR MAESTRE RAMIREZ
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile serviceCall Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile servicerehmti665
 

Recently uploaded (20)

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
 
Biology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptxBiology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptx
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptx
 
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
 
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
 
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
 
main PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfidmain PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfid
 
Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineering
 
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
 
young call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Service
young call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Serviceyoung call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Service
young call girls in Rajiv Chowk🔝 9953056974 🔝 Delhi escort Service
 
Heart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptxHeart Disease Prediction using machine learning.pptx
Heart Disease Prediction using machine learning.pptx
 
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANVI) Koregaon Park Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
 
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptxExploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
Exploring_Network_Security_with_JA3_by_Rakesh Seal.pptx
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.
 
Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile serviceCall Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile service
 
🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...
🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...
🔝9953056974🔝!!-YOUNG call girls in Rajendra Nagar Escort rvice Shot 2000 nigh...
 

Introduction of predicate logics

  • 1. Introduction of Predicate Logics Prof. Neeraj Bhargava Kapil Chauhan Department of Computer Science School of Engineering & Systems Sciences MDS University, Ajmer
  • 2. Outline  Intro of Predicate logic  Connectives  Quantifiers  Syntax of PL  Semantics of PL  Some useful equivalences
  • 3. Predicate Symbols and Signatures  Predicate symbols represent relations between zero or more objects  The number of objects define a predicate‘s aritiy  Examples:  Likes(george, kate)  Likes(x,x)  Likes(joe, kate, susy)  Friends (father_of(david), father_of(andrew))  Signature: A signature is a collection of constants, function symbols and predicate symbols with specified arities
  • 4. Connectives  FOL formulas are joined together by logical operators to form more complex formulas (just like in propositional logic)  The basic logical operators are the same as in propositional logic as well:  Negation: ¬p („it is not the case that p“)  Conjunction: p ∧ q („p and q“)  Disjunction: p ∨ q („p or q“)  Implication: p → q („p implies q“ or “q if p“)  Equivalence: p ↔ q („p if and only if q“)
  • 5. Quantifiers  Two quantifiers: Universal (∀) and Existential (∃)  Allow us to express properties of collections of objects instead of enumerating objects by name  Apply to sentence containing variable  Universal ∀: true for all substitutions for the variable  “for all”: ∀<variables> <sentence>  Existential ∃: true for at least one substitution for the variable  “there exists”: ∃<variables> <sentence>  Examples:  ∃ x: Mother(art) = x  ∀ x ∀ y: Mother(x) = Mother(y) → Sibling(x,y)  ∃ y ∃ x: Mother(y) = x
  • 6. Predicate logic, syntax  The syntax in Luger is inspired by Prolog  Propositions are replaced by –  Predicate symbols (with arity) (p, q, r, …)  – Terms, made of  Constants (a, b, c, …)  Variables (x, y, z, …)  Function symbols (with arity) (f, g, h, …)  Quantifiers ∀ (for all) and ∃ (exists)  If ϕ is a sentence and x a variable, then ∀x:ϕ and ∃x:ϕ are sentences.
  • 7. Predicate logic, semantics  Interpret terms as elements of a domain D.  Interpretation I:  • Constant: element of D.  • Function symbol with arity n: D n → D.  Valuation v:  Variable: element of D.  Interpret predicate symbols with arity n as subsets of Dn Example: I(parent) = {(x,y) | x is the parent of y}.
  • 8. Predicate logic, semantics  If ϕ is a sentence, then ¬ϕ is T under I,v iff ϕ is F under I,v ... ∀x:ϕ is T under I,v iff ϕ is T under I,v’, for all valuations v’ that differ from v only at x ∃x:ϕ is T under I,v iff ϕ is T under I,v’, for some valuation v’ that differs from v only at x
  • 9. Some useful equivalence  Elimination: ∃x:p(x) ≡ ¬∀x:¬p(x) also: ¬∃x:p(x) ≡ ∀x:¬p(x), ¬∀x:p(x) ≡ ∃x:¬p(x), • • Names of variables can be changed: ∃x:p(x) ≡ ∃y:p(y), ∀x:p(x) ≡ ∀y:p(y) • • ∀x:(p(x) ∧ q(x)) ≡ ∀x:p(x) ∧ ∀x:q(x) - not for ∨! • • ∃x:(p(x) ∨ q(x)) ≡ ∃x:p(x) ∨ ∃x:q(x) - not for ∧!
  • 10. Formulas  The set of formulas is inductively defined by the following rules: 1. Preciate symbols: If P is an n-ary predicate symbol and t1,…,tn are terms then P(t1,…,tn) is a formula. 2. Negation: If φ is a formula, then ¬φ is a formula 3. Binary connectives: If φ and ψ are formulas, then (φ → ψ) is a formula. Same for other binary logical connectives. 4. Quantifiers: If φ is a formula and x is a variable, then ∀xφ and ∃xφ are formulas.  Atomic formulas are formulas obtained only using the first rule  Example: If f is a unary function symbol, P a unary predicate symbol, and Q a ternary predicate symbol, then the following is a formula: ∀x∀y(P(f(x)) → ¬(P(x)) → Q(f(y), x, x)))
  • 11. Formulas  Any occurrence of a variable in a formulate not in the scope of a quantifier is said to be a free occurrence  Otherwise it is called a bound occurrence  Thus, if x is a free variable in φ, it is bound in ∀xφ and ∃xφ  A formula with no free variables is called a closed formula  Example: x and y are bound variables, z is a free variable ∀x∀y(P(f(x)) → ¬(P(x)) → Q(f(y), x, z)))
  • 12. Assignment  Describe the predicate logic in logic of AI and discuss the useful formulas to design facts.