SlideShare a Scribd company logo
Topic To Be Covered:
First Order Logic(Part-03)
1.Unification 2.Resolution In FOL
Jagdamba Education Society's
SND College of Engineering & Research Centre
Department of Computer Engineering
SUBJECT: Artificial Intelligence & Robotics
Lecture No-1(UNIT-03)
Logic & Reasoning
Prof.Dhakane Vikas N
What is Unification
Unification
 Unification is a process of making two different logical atomic expressions
identical by finding a substitution.
 Unification depends on the substitution process.
 It takes two literals as input and makes them identical using substitution.
What is Unification
Unification :Conditions for Unification:
Following are some basic conditions for unification:
1. Predicate symbol must be same, atoms or expression with different
predicate symbol can never be unified.
2. Number of Arguments in both expressions must be identical.
3. Unification will fail if there are two similar variables present in the same
expression.
What is Unification
Unification :Example
E.g. Let's say there are two different expressions,
P(x, y), and P(a, f(z)).
 In this example, we need to make both above statements identical to
each other. For this, we will perform the substitution.
P(x, y)......... (i)
P(a, f(z))......... (ii)
 Substitute x with a, and y with f(z) in the first expression, and it
will be represented as a/x and f(z)/y.
 With both the substitutions, the first expression will be identical to
the second expression and the substitution set will be: [a/x, f(z)/y].
What is Unification
Unification :Example
We can resolve two clauses which are given below:
[Animal (g(x) V Loves (f(x), x)] and [¬ Loves(a, b) V ¬Kills(a, b)]
Where two complimentary literals are: Loves (f(x), x) and ¬ Loves
(a, b)
These literals can be unified with unifier : [a/f(x), and b/x] , and it
What is Unification(Unification :Algorithm)
Resolution in FOL
Resolution in FOL
 Resolution is a theorem proving technique that proceeds by building
refutation proofs, i.e., proofs by contradictions.
 It was invented by a Mathematician John Alan Robinson in the year 1965.
 Resolution is used, if there are various statements are given, and we need
to prove a conclusion of those statements.
 Unification is a key concept in proofs by resolutions.
 Resolution is a single inference rule which can efficiently operate on the
conjunctive normal form or clausal form.
Resolution in FOL
Resolution in FOL
 Clause: Disjunction of literals (an atomic sentence) is called a clause. It is
also known as a unit clause.
 Conjunctive Normal Form: A sentence represented as a conjunction of
clauses is said to be conjunctive normal form or CNF.
Example:
 We can resolve two clauses which are given below:
 [Animal (g(x) V Loves (f(x), x)] and [¬ Loves(a, b) V ¬Kills(a, b)]
 Where two complimentary literals are: Loves (f(x), x) and ¬ Loves (a, b)
 These literals can be unified with unifier θ= [a/f(x), and b/x] , and it will
generate a resolvent clause:
[Animal (g(x) V ¬ Kills(f(x), x)].
Resolution in FOL
Resolution in FOL
Steps for Resolution:
1. Conversion of facts into first-order logic.
2. Convert FOL statements into CNF
3. Negate the statement which needs to prove (proof by
contradiction)
4. Draw resolution graph (unification).
To better understand all the above steps, we will take an example in
which we will apply resolution.
Resolution in FOL
Resolution in FOL
Steps for Resolution: Convert FOL statements into CNF
Ai lecture  11(unit03)

More Related Content

PPTX
Log Transformation in Image Processing with Example
PDF
Bayes Belief Networks
PPTX
Ensemble learning
PPTX
Object Detection using Deep Neural Networks
PPTX
Local beam search example
PDF
Syntactic analysis in NLP
ODP
Computational Intelligence and Applications
PPTX
Artificial Intelligence
Log Transformation in Image Processing with Example
Bayes Belief Networks
Ensemble learning
Object Detection using Deep Neural Networks
Local beam search example
Syntactic analysis in NLP
Computational Intelligence and Applications
Artificial Intelligence

What's hot (20)

PPTX
Ensemble methods in machine learning
PPT
Introduction to prolog
PPT
Cocomo model
PPTX
Context free grammar
PPTX
Introduction to Deep Learning
PPT
Finite automata examples
PPSX
Edge Detection and Segmentation
PDF
Dimensionality Reduction
PDF
Introduction to Generative Adversarial Networks (GANs)
PPTX
Genetic Algorithm in Artificial Intelligence
PPTX
Lecture 1: Semantic Analysis in Language Technology
PPTX
Naïve Bayes Classifier Algorithm.pptx
PPTX
Convolution Neural Network (CNN)
PDF
A Review of Deep Contextualized Word Representations (Peters+, 2018)
PPTX
Recurrent Neural Networks (RNNs)
PDF
Region Splitting and Merging Technique For Image segmentation.
PPTX
RECURSIVE DESCENT PARSING
PDF
PDF
Text summarization
PPTX
Directed Acyclic Graph Representation of basic blocks
Ensemble methods in machine learning
Introduction to prolog
Cocomo model
Context free grammar
Introduction to Deep Learning
Finite automata examples
Edge Detection and Segmentation
Dimensionality Reduction
Introduction to Generative Adversarial Networks (GANs)
Genetic Algorithm in Artificial Intelligence
Lecture 1: Semantic Analysis in Language Technology
Naïve Bayes Classifier Algorithm.pptx
Convolution Neural Network (CNN)
A Review of Deep Contextualized Word Representations (Peters+, 2018)
Recurrent Neural Networks (RNNs)
Region Splitting and Merging Technique For Image segmentation.
RECURSIVE DESCENT PARSING
Text summarization
Directed Acyclic Graph Representation of basic blocks
Ad

More from vikas dhakane (20)

PDF
Ai lecture 14(unit03)
PPTX
Ai lecture 13(unit03)
PDF
Ai lecture 13(unit03)
PPTX
Ai lecture 12(unit03)
PDF
Ai lecture 12(unit03)
PDF
Ai lecture 11(unit03)
PPTX
Ai lecture 10(unit03)
PDF
Ai lecture 10(unit03)
PDF
Ai lecture 09(unit03)
PDF
Ai lecture 07(unit03)
PPTX
Ai lecture 05(unit03)
PDF
Ai lecture 05(unit03)
PPTX
Ai lecture 04(unit03)
PDF
Ai lecture 04(unit03)
PPTX
Ai lecture 03(unit03)
PDF
Ai lecture 03(unit03)
PPTX
Ai lecture 003(unit03)
PDF
Ai lecture 003(unit03)
PPTX
Ai lecture 02(unit03)
PPTX
Ai lecture 01(unit03)
Ai lecture 14(unit03)
Ai lecture 13(unit03)
Ai lecture 13(unit03)
Ai lecture 12(unit03)
Ai lecture 12(unit03)
Ai lecture 11(unit03)
Ai lecture 10(unit03)
Ai lecture 10(unit03)
Ai lecture 09(unit03)
Ai lecture 07(unit03)
Ai lecture 05(unit03)
Ai lecture 05(unit03)
Ai lecture 04(unit03)
Ai lecture 04(unit03)
Ai lecture 03(unit03)
Ai lecture 03(unit03)
Ai lecture 003(unit03)
Ai lecture 003(unit03)
Ai lecture 02(unit03)
Ai lecture 01(unit03)
Ad

Ai lecture 11(unit03)

  • 1. Topic To Be Covered: First Order Logic(Part-03) 1.Unification 2.Resolution In FOL Jagdamba Education Society's SND College of Engineering & Research Centre Department of Computer Engineering SUBJECT: Artificial Intelligence & Robotics Lecture No-1(UNIT-03) Logic & Reasoning Prof.Dhakane Vikas N
  • 2. What is Unification Unification  Unification is a process of making two different logical atomic expressions identical by finding a substitution.  Unification depends on the substitution process.  It takes two literals as input and makes them identical using substitution.
  • 3. What is Unification Unification :Conditions for Unification: Following are some basic conditions for unification: 1. Predicate symbol must be same, atoms or expression with different predicate symbol can never be unified. 2. Number of Arguments in both expressions must be identical. 3. Unification will fail if there are two similar variables present in the same expression.
  • 4. What is Unification Unification :Example E.g. Let's say there are two different expressions, P(x, y), and P(a, f(z)).  In this example, we need to make both above statements identical to each other. For this, we will perform the substitution. P(x, y)......... (i) P(a, f(z))......... (ii)  Substitute x with a, and y with f(z) in the first expression, and it will be represented as a/x and f(z)/y.  With both the substitutions, the first expression will be identical to the second expression and the substitution set will be: [a/x, f(z)/y].
  • 5. What is Unification Unification :Example We can resolve two clauses which are given below: [Animal (g(x) V Loves (f(x), x)] and [¬ Loves(a, b) V ¬Kills(a, b)] Where two complimentary literals are: Loves (f(x), x) and ¬ Loves (a, b) These literals can be unified with unifier : [a/f(x), and b/x] , and it
  • 7. Resolution in FOL Resolution in FOL  Resolution is a theorem proving technique that proceeds by building refutation proofs, i.e., proofs by contradictions.  It was invented by a Mathematician John Alan Robinson in the year 1965.  Resolution is used, if there are various statements are given, and we need to prove a conclusion of those statements.  Unification is a key concept in proofs by resolutions.  Resolution is a single inference rule which can efficiently operate on the conjunctive normal form or clausal form.
  • 8. Resolution in FOL Resolution in FOL  Clause: Disjunction of literals (an atomic sentence) is called a clause. It is also known as a unit clause.  Conjunctive Normal Form: A sentence represented as a conjunction of clauses is said to be conjunctive normal form or CNF. Example:  We can resolve two clauses which are given below:  [Animal (g(x) V Loves (f(x), x)] and [¬ Loves(a, b) V ¬Kills(a, b)]  Where two complimentary literals are: Loves (f(x), x) and ¬ Loves (a, b)  These literals can be unified with unifier θ= [a/f(x), and b/x] , and it will generate a resolvent clause: [Animal (g(x) V ¬ Kills(f(x), x)].
  • 9. Resolution in FOL Resolution in FOL Steps for Resolution: 1. Conversion of facts into first-order logic. 2. Convert FOL statements into CNF 3. Negate the statement which needs to prove (proof by contradiction) 4. Draw resolution graph (unification). To better understand all the above steps, we will take an example in which we will apply resolution.
  • 10. Resolution in FOL Resolution in FOL Steps for Resolution: Convert FOL statements into CNF