SlideShare a Scribd company logo
ARTIFICAL INTELLIGENCE
(R18 III(II Sem))
Department of computer science and
engineering (AI/ML)
Session 18
by
Asst.Prof.M.Gokilavani
VITS
4/25/2023 Dpaertment of CSE ( AL & ML) 1
TEXTBOOK:
• Artificial Intelligence A modern Approach, Third
Edition, Stuart Russell and Peter Norvig, Pearson
Education.
REFERENCES:
• Artificial Intelligence, 3rd Edn, E. Rich and
K.Knight (TMH).
• Artificial Intelligence, 3rd Edn, Patrick Henny
Winston, Pearson Education.
• Artificial Intelligence, Shivani Goel, Pearson
Education.
• Artificial Intelligence and Expert Systems-
Patterson, Pearson Education.
4/25/2023 Dpaertment of CSE ( AL & ML) 2
Topics covered in session 18
• Adversarial Search: Games, Optimal Decisions in Games, Alpha–
Beta Pruning, Imperfect Real-Time Decisions.
• Constraint Satisfaction Problems: Defining Constraint
Satisfaction Problems, Constraint Propagation, Backtracking
Search for CSPs, Local Search for CSPs, The Structure of
Problems.
• Propositional Logic: Knowledge-Based Agents, The Wumpus
World, Logic, Propositional Logic, Propositional Theorem
Proving: Inference and proofs, Proof by resolution, Horn clauses
and definite clauses, Forward and backward chaining, Effective
Propositional Model Checking, Agents Based on Propositional
Logic.
4/25/2023 Dpaertment of CSE ( AL & ML) 3
Cryptarithmetic Problem
• Cryptarithmetic Problem is a type of constraint
satisfaction problem where the game is about digits and
its unique replacement either with alphabets or other
symbols.
• In cryptarithmetic problem, the digits (0-9) get
substituted by some possible alphabets or symbols.
• The task in cryptarithmetic problem is to substitute
each digit with an alphabet to get the result
arithmetically correct.
• We can perform all the arithmetic operations on a given
cryptarithmetic problem.
4/25/2023 4
Dpaertment of CSE ( AL & ML)
Constraints for cryptarithmetic
problem
• Unique digit to be replaced with a unique alphabet
(no repeated digits).
• The result should satisfy the predefined arithmetic
rules, i.e., 2+2 =4
• Digits should be from 0-9 only.
• In addition operation only one carry forward.
• The problem can be solved from both sides,
i.e., lefthand side (L.H.S), or right-hand side
(R.H.S)
4/25/2023 5
Dpaertment of CSE ( AL & ML)
Example 1
• Given a cryptarithmetic problem, i.e., S E N D
+ M O R E = M O N E Y.
4/25/2023 6
Dpaertment of CSE ( AL & ML)
4/25/2023 Dpaertment of CSE ( AL & ML) 7
Step 1
4/25/2023 8
Dpaertment of CSE ( AL & ML)
• Starting from the left hand side (L.H.S) , the terms
are S and M. Assign a digit which could give a
satisfactory result. Let’s assign S->9 and M->1.
Hence, we get a satisfactory result by adding up the
terms and got an assignment for O as O->0 as well.
Step 2
• Now, move ahead to the next terms E and O to
get N as its output.
4/25/2023 9
Dpaertment of CSE ( AL & ML)
Adding E and O, which means 5+0=0, which is not
possible because we cannot assign the same digit to
two letters.
• Add carry 1 to the value E to change the
value of alphabet.
4/25/2023 10
Dpaertment of CSE ( AL & ML)
Step 3
4/25/2023 11
Dpaertment of CSE ( AL & ML)
• Further, adding the next two terms N and R we get,
But, we have already assigned E->5. Not possible with 5 to E
Again, after solving the whole problem, we will get a
carryover on this term, so our answer will be satisfied.
Step 4
• Again, on adding the last two terms, i.e., the
rightmost terms D and E, we get Y as its result.
4/25/2023 12
Dpaertment of CSE ( AL & ML)
• Keeping all the constraints in mind, the final resultant
is as follows:
4/25/2023 13
Dpaertment of CSE ( AL & ML)
Alphabets Values
S 9
E 5
N 6
D 7
M 1
O 0
R 8
Y 2
Example 2
4/25/2023 14
Dpaertment of CSE ( AL & ML)
Example 3
4/25/2023 15
Dpaertment of CSE ( AL & ML)
Topics to be covered in next
session 19
• Backtracking CSP’s
Thank you!!!
4/25/2023 Dpaertment of CSE ( AL & ML) 16

More Related Content

What's hot

Knowledge representation in AI
Knowledge representation in AIKnowledge representation in AI
Knowledge representation in AIVishal Singh
 
AI: Planning and AI
AI: Planning and AIAI: Planning and AI
AI: Planning and AI
DataminingTools Inc
 
Unit4: Knowledge Representation
Unit4: Knowledge RepresentationUnit4: Knowledge Representation
Unit4: Knowledge Representation
Tekendra Nath Yogi
 
I. Mini-Max Algorithm in AI
I. Mini-Max Algorithm in AII. Mini-Max Algorithm in AI
I. Mini-Max Algorithm in AI
vikas dhakane
 
Genetic Algorithms
Genetic AlgorithmsGenetic Algorithms
Genetic Algorithms
Alaa Khamis, PhD, SMIEEE
 
knowledge representation using rules
knowledge representation using rulesknowledge representation using rules
knowledge representation using rules
Harini Balamurugan
 
tic-tac-toe: Game playing
 tic-tac-toe: Game playing tic-tac-toe: Game playing
tic-tac-toe: Game playing
kalpana Manudhane
 
AI search techniques
AI search techniquesAI search techniques
AI search techniques
Omar Isaid
 
Knowledge based agents
Knowledge based agentsKnowledge based agents
Knowledge based agents
Megha Sharma
 
Semantic nets in artificial intelligence
Semantic nets in artificial intelligenceSemantic nets in artificial intelligence
Semantic nets in artificial intelligence
harshita virwani
 
Genetic Algorithms
Genetic AlgorithmsGenetic Algorithms
Genetic Algorithms
Karthik Sankar
 
I. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithmI. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithm
vikas dhakane
 
AI_Session 21 First order logic.pptx
AI_Session 21 First order logic.pptxAI_Session 21 First order logic.pptx
AI_Session 21 First order logic.pptx
Asst.prof M.Gokilavani
 
Knowledge based agents
Knowledge based agentsKnowledge based agents
Knowledge based agents
Dr. C.V. Suresh Babu
 
AI: Learning in AI
AI: Learning in AI AI: Learning in AI
AI: Learning in AI
DataminingTools Inc
 
Minmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slidesMinmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slides
SamiaAziz4
 
Mathematical Analysis of Recursive Algorithm.
Mathematical Analysis of Recursive Algorithm.Mathematical Analysis of Recursive Algorithm.
Mathematical Analysis of Recursive Algorithm.
mohanrathod18
 
Unit 2 ai
Unit 2 aiUnit 2 ai
Unit 2 ai
Jeevan Chapagain
 
AI_Session 20 Horn clause.pptx
AI_Session 20 Horn clause.pptxAI_Session 20 Horn clause.pptx
AI_Session 20 Horn clause.pptx
Asst.prof M.Gokilavani
 

What's hot (20)

Knowledge representation in AI
Knowledge representation in AIKnowledge representation in AI
Knowledge representation in AI
 
AI: Planning and AI
AI: Planning and AIAI: Planning and AI
AI: Planning and AI
 
Unit4: Knowledge Representation
Unit4: Knowledge RepresentationUnit4: Knowledge Representation
Unit4: Knowledge Representation
 
I. Mini-Max Algorithm in AI
I. Mini-Max Algorithm in AII. Mini-Max Algorithm in AI
I. Mini-Max Algorithm in AI
 
Genetic Algorithms
Genetic AlgorithmsGenetic Algorithms
Genetic Algorithms
 
knowledge representation using rules
knowledge representation using rulesknowledge representation using rules
knowledge representation using rules
 
tic-tac-toe: Game playing
 tic-tac-toe: Game playing tic-tac-toe: Game playing
tic-tac-toe: Game playing
 
AI search techniques
AI search techniquesAI search techniques
AI search techniques
 
Knowledge based agents
Knowledge based agentsKnowledge based agents
Knowledge based agents
 
Semantic nets in artificial intelligence
Semantic nets in artificial intelligenceSemantic nets in artificial intelligence
Semantic nets in artificial intelligence
 
Language models
Language modelsLanguage models
Language models
 
Genetic Algorithms
Genetic AlgorithmsGenetic Algorithms
Genetic Algorithms
 
I. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithmI. Hill climbing algorithm II. Steepest hill climbing algorithm
I. Hill climbing algorithm II. Steepest hill climbing algorithm
 
AI_Session 21 First order logic.pptx
AI_Session 21 First order logic.pptxAI_Session 21 First order logic.pptx
AI_Session 21 First order logic.pptx
 
Knowledge based agents
Knowledge based agentsKnowledge based agents
Knowledge based agents
 
AI: Learning in AI
AI: Learning in AI AI: Learning in AI
AI: Learning in AI
 
Minmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slidesMinmax Algorithm In Artificial Intelligence slides
Minmax Algorithm In Artificial Intelligence slides
 
Mathematical Analysis of Recursive Algorithm.
Mathematical Analysis of Recursive Algorithm.Mathematical Analysis of Recursive Algorithm.
Mathematical Analysis of Recursive Algorithm.
 
Unit 2 ai
Unit 2 aiUnit 2 ai
Unit 2 ai
 
AI_Session 20 Horn clause.pptx
AI_Session 20 Horn clause.pptxAI_Session 20 Horn clause.pptx
AI_Session 20 Horn clause.pptx
 

Similar to AI_Session 18 Cryptoarithmetic problem.pptx

AI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptx
AI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptxAI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptx
AI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptx
Asst.prof M.Gokilavani
 
AI_Session 17 CSP.pptx
AI_Session 17 CSP.pptxAI_Session 17 CSP.pptx
AI_Session 17 CSP.pptx
Asst.prof M.Gokilavani
 
AI_Session 16 imperfect Real time decisons .pptx
AI_Session 16 imperfect Real time decisons .pptxAI_Session 16 imperfect Real time decisons .pptx
AI_Session 16 imperfect Real time decisons .pptx
Asst.prof M.Gokilavani
 
Sat math overview from college board
Sat math overview from college boardSat math overview from college board
Sat math overview from college boardJSlinkyNY
 
Sat math overview from college board
Sat math overview from college boardSat math overview from college board
Sat math overview from college boardYoAmoNYC
 
AI_session 23 Resolution.pptx
AI_session 23 Resolution.pptxAI_session 23 Resolution.pptx
AI_session 23 Resolution.pptx
Asst.prof M.Gokilavani
 
Class X Mathematics Study Material
Class X Mathematics Study MaterialClass X Mathematics Study Material
Class X Mathematics Study Material
FellowBuddy.com
 
Algorithms
AlgorithmsAlgorithms
Algorithms
DrHiyamHatem
 
Combinatorics.ppt
Combinatorics.pptCombinatorics.ppt
Combinatorics.ppt
ssuserdc5a3d
 
Backtracking based integer factorisation, primality testing and square root c...
Backtracking based integer factorisation, primality testing and square root c...Backtracking based integer factorisation, primality testing and square root c...
Backtracking based integer factorisation, primality testing and square root c...
csandit
 
AI_Session 19 Backtracking CSP.pptx
AI_Session 19 Backtracking CSP.pptxAI_Session 19 Backtracking CSP.pptx
AI_Session 19 Backtracking CSP.pptx
Asst.prof M.Gokilavani
 
AI3391 Artificial Intelligence Session 21 CSP.pptx
AI3391 Artificial Intelligence Session 21 CSP.pptxAI3391 Artificial Intelligence Session 21 CSP.pptx
AI3391 Artificial Intelligence Session 21 CSP.pptx
Asst.prof M.Gokilavani
 
Constraint satisfaction problems (csp)
Constraint satisfaction problems (csp)   Constraint satisfaction problems (csp)
Constraint satisfaction problems (csp)
Archana432045
 
CSP.pptx
CSP.pptxCSP.pptx
CSP.pptx
jainam bhavsar
 
Computer Science syllabus
Computer Science syllabusComputer Science syllabus
Computer Science syllabus
Shivaraj Hugar
 
MATH7 ADM MODULE 3.pdf
MATH7 ADM MODULE 3.pdfMATH7 ADM MODULE 3.pdf
MATH7 ADM MODULE 3.pdf
NelsonNelson56
 
Pptdec2
Pptdec2Pptdec2
Pptdec2
Pptdec2Pptdec2
2003 book discrete_mathematics
2003 book discrete_mathematics2003 book discrete_mathematics
2003 book discrete_mathematics
VladimirMoyanoFiguer
 

Similar to AI_Session 18 Cryptoarithmetic problem.pptx (20)

AI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptx
AI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptxAI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptx
AI3391 Artificial intelligence Session 22 Cryptarithmetic problem.pptx
 
AI_Session 17 CSP.pptx
AI_Session 17 CSP.pptxAI_Session 17 CSP.pptx
AI_Session 17 CSP.pptx
 
AI Lesson 09
AI Lesson 09AI Lesson 09
AI Lesson 09
 
AI_Session 16 imperfect Real time decisons .pptx
AI_Session 16 imperfect Real time decisons .pptxAI_Session 16 imperfect Real time decisons .pptx
AI_Session 16 imperfect Real time decisons .pptx
 
Sat math overview from college board
Sat math overview from college boardSat math overview from college board
Sat math overview from college board
 
Sat math overview from college board
Sat math overview from college boardSat math overview from college board
Sat math overview from college board
 
AI_session 23 Resolution.pptx
AI_session 23 Resolution.pptxAI_session 23 Resolution.pptx
AI_session 23 Resolution.pptx
 
Class X Mathematics Study Material
Class X Mathematics Study MaterialClass X Mathematics Study Material
Class X Mathematics Study Material
 
Algorithms
AlgorithmsAlgorithms
Algorithms
 
Combinatorics.ppt
Combinatorics.pptCombinatorics.ppt
Combinatorics.ppt
 
Backtracking based integer factorisation, primality testing and square root c...
Backtracking based integer factorisation, primality testing and square root c...Backtracking based integer factorisation, primality testing and square root c...
Backtracking based integer factorisation, primality testing and square root c...
 
AI_Session 19 Backtracking CSP.pptx
AI_Session 19 Backtracking CSP.pptxAI_Session 19 Backtracking CSP.pptx
AI_Session 19 Backtracking CSP.pptx
 
AI3391 Artificial Intelligence Session 21 CSP.pptx
AI3391 Artificial Intelligence Session 21 CSP.pptxAI3391 Artificial Intelligence Session 21 CSP.pptx
AI3391 Artificial Intelligence Session 21 CSP.pptx
 
Constraint satisfaction problems (csp)
Constraint satisfaction problems (csp)   Constraint satisfaction problems (csp)
Constraint satisfaction problems (csp)
 
CSP.pptx
CSP.pptxCSP.pptx
CSP.pptx
 
Computer Science syllabus
Computer Science syllabusComputer Science syllabus
Computer Science syllabus
 
MATH7 ADM MODULE 3.pdf
MATH7 ADM MODULE 3.pdfMATH7 ADM MODULE 3.pdf
MATH7 ADM MODULE 3.pdf
 
Pptdec2
Pptdec2Pptdec2
Pptdec2
 
Pptdec2
Pptdec2Pptdec2
Pptdec2
 
2003 book discrete_mathematics
2003 book discrete_mathematics2003 book discrete_mathematics
2003 book discrete_mathematics
 

More from Asst.prof M.Gokilavani

CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete RecordCCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
Asst.prof M.Gokilavani
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
Asst.prof M.Gokilavani
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
Asst.prof M.Gokilavani
 
CCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdf
CCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdfCCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdf
CCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdf
Asst.prof M.Gokilavani
 
IT8073_Information Security_UNIT I _.pdf
IT8073_Information Security_UNIT I _.pdfIT8073_Information Security_UNIT I _.pdf
IT8073_Information Security_UNIT I _.pdf
Asst.prof M.Gokilavani
 
IT8073 _Information Security _UNIT I Full notes
IT8073 _Information Security _UNIT I Full notesIT8073 _Information Security _UNIT I Full notes
IT8073 _Information Security _UNIT I Full notes
Asst.prof M.Gokilavani
 
GE3151 PSPP UNIT IV QUESTION BANK.docx.pdf
GE3151 PSPP UNIT IV QUESTION BANK.docx.pdfGE3151 PSPP UNIT IV QUESTION BANK.docx.pdf
GE3151 PSPP UNIT IV QUESTION BANK.docx.pdf
Asst.prof M.Gokilavani
 
GE3151 PSPP UNIT III QUESTION BANK.docx.pdf
GE3151 PSPP UNIT III QUESTION BANK.docx.pdfGE3151 PSPP UNIT III QUESTION BANK.docx.pdf
GE3151 PSPP UNIT III QUESTION BANK.docx.pdf
Asst.prof M.Gokilavani
 
GE3151 UNIT II Study material .pdf
GE3151 UNIT II Study material .pdfGE3151 UNIT II Study material .pdf
GE3151 UNIT II Study material .pdf
Asst.prof M.Gokilavani
 
GE3151 PSPP All unit question bank.pdf
GE3151 PSPP All unit question bank.pdfGE3151 PSPP All unit question bank.pdf
GE3151 PSPP All unit question bank.pdf
Asst.prof M.Gokilavani
 
GE3151_PSPP_All unit _Notes
GE3151_PSPP_All unit _NotesGE3151_PSPP_All unit _Notes
GE3151_PSPP_All unit _Notes
Asst.prof M.Gokilavani
 
GE3151_PSPP_UNIT_5_Notes
GE3151_PSPP_UNIT_5_NotesGE3151_PSPP_UNIT_5_Notes
GE3151_PSPP_UNIT_5_Notes
Asst.prof M.Gokilavani
 
GE3151_PSPP_UNIT_4_Notes
GE3151_PSPP_UNIT_4_NotesGE3151_PSPP_UNIT_4_Notes
GE3151_PSPP_UNIT_4_Notes
Asst.prof M.Gokilavani
 
GE3151_PSPP_UNIT_3_Notes
GE3151_PSPP_UNIT_3_NotesGE3151_PSPP_UNIT_3_Notes
GE3151_PSPP_UNIT_3_Notes
Asst.prof M.Gokilavani
 
GE3151_PSPP_UNIT_2_Notes
GE3151_PSPP_UNIT_2_NotesGE3151_PSPP_UNIT_2_Notes
GE3151_PSPP_UNIT_2_Notes
Asst.prof M.Gokilavani
 
AI3391 Artificial intelligence Unit IV Notes _ merged.pdf
AI3391 Artificial intelligence Unit IV Notes _ merged.pdfAI3391 Artificial intelligence Unit IV Notes _ merged.pdf
AI3391 Artificial intelligence Unit IV Notes _ merged.pdf
Asst.prof M.Gokilavani
 
AI3391 Artificial intelligence Session 29 Forward and backward chaining.pdf
AI3391 Artificial intelligence Session 29 Forward and backward chaining.pdfAI3391 Artificial intelligence Session 29 Forward and backward chaining.pdf
AI3391 Artificial intelligence Session 29 Forward and backward chaining.pdf
Asst.prof M.Gokilavani
 
AI3391 Artificial intelligence Session 28 Resolution.pptx
AI3391 Artificial intelligence Session 28 Resolution.pptxAI3391 Artificial intelligence Session 28 Resolution.pptx
AI3391 Artificial intelligence Session 28 Resolution.pptx
Asst.prof M.Gokilavani
 
AI3391 Artificial intelligence session 27 inference and unification.pptx
AI3391 Artificial intelligence session 27 inference and unification.pptxAI3391 Artificial intelligence session 27 inference and unification.pptx
AI3391 Artificial intelligence session 27 inference and unification.pptx
Asst.prof M.Gokilavani
 
AI3391 Artificial Intelligence Session 26 First order logic.pptx
AI3391 Artificial Intelligence Session 26 First order logic.pptxAI3391 Artificial Intelligence Session 26 First order logic.pptx
AI3391 Artificial Intelligence Session 26 First order logic.pptx
Asst.prof M.Gokilavani
 

More from Asst.prof M.Gokilavani (20)

CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete RecordCCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
CCS335 _ Neural Networks and Deep Learning Laboratory_Lab Complete Record
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
 
CCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdf
CCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdfCCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdf
CCS355 Neural Networks & Deep Learning Unit 1 PDF notes with Question bank .pdf
 
IT8073_Information Security_UNIT I _.pdf
IT8073_Information Security_UNIT I _.pdfIT8073_Information Security_UNIT I _.pdf
IT8073_Information Security_UNIT I _.pdf
 
IT8073 _Information Security _UNIT I Full notes
IT8073 _Information Security _UNIT I Full notesIT8073 _Information Security _UNIT I Full notes
IT8073 _Information Security _UNIT I Full notes
 
GE3151 PSPP UNIT IV QUESTION BANK.docx.pdf
GE3151 PSPP UNIT IV QUESTION BANK.docx.pdfGE3151 PSPP UNIT IV QUESTION BANK.docx.pdf
GE3151 PSPP UNIT IV QUESTION BANK.docx.pdf
 
GE3151 PSPP UNIT III QUESTION BANK.docx.pdf
GE3151 PSPP UNIT III QUESTION BANK.docx.pdfGE3151 PSPP UNIT III QUESTION BANK.docx.pdf
GE3151 PSPP UNIT III QUESTION BANK.docx.pdf
 
GE3151 UNIT II Study material .pdf
GE3151 UNIT II Study material .pdfGE3151 UNIT II Study material .pdf
GE3151 UNIT II Study material .pdf
 
GE3151 PSPP All unit question bank.pdf
GE3151 PSPP All unit question bank.pdfGE3151 PSPP All unit question bank.pdf
GE3151 PSPP All unit question bank.pdf
 
GE3151_PSPP_All unit _Notes
GE3151_PSPP_All unit _NotesGE3151_PSPP_All unit _Notes
GE3151_PSPP_All unit _Notes
 
GE3151_PSPP_UNIT_5_Notes
GE3151_PSPP_UNIT_5_NotesGE3151_PSPP_UNIT_5_Notes
GE3151_PSPP_UNIT_5_Notes
 
GE3151_PSPP_UNIT_4_Notes
GE3151_PSPP_UNIT_4_NotesGE3151_PSPP_UNIT_4_Notes
GE3151_PSPP_UNIT_4_Notes
 
GE3151_PSPP_UNIT_3_Notes
GE3151_PSPP_UNIT_3_NotesGE3151_PSPP_UNIT_3_Notes
GE3151_PSPP_UNIT_3_Notes
 
GE3151_PSPP_UNIT_2_Notes
GE3151_PSPP_UNIT_2_NotesGE3151_PSPP_UNIT_2_Notes
GE3151_PSPP_UNIT_2_Notes
 
AI3391 Artificial intelligence Unit IV Notes _ merged.pdf
AI3391 Artificial intelligence Unit IV Notes _ merged.pdfAI3391 Artificial intelligence Unit IV Notes _ merged.pdf
AI3391 Artificial intelligence Unit IV Notes _ merged.pdf
 
AI3391 Artificial intelligence Session 29 Forward and backward chaining.pdf
AI3391 Artificial intelligence Session 29 Forward and backward chaining.pdfAI3391 Artificial intelligence Session 29 Forward and backward chaining.pdf
AI3391 Artificial intelligence Session 29 Forward and backward chaining.pdf
 
AI3391 Artificial intelligence Session 28 Resolution.pptx
AI3391 Artificial intelligence Session 28 Resolution.pptxAI3391 Artificial intelligence Session 28 Resolution.pptx
AI3391 Artificial intelligence Session 28 Resolution.pptx
 
AI3391 Artificial intelligence session 27 inference and unification.pptx
AI3391 Artificial intelligence session 27 inference and unification.pptxAI3391 Artificial intelligence session 27 inference and unification.pptx
AI3391 Artificial intelligence session 27 inference and unification.pptx
 
AI3391 Artificial Intelligence Session 26 First order logic.pptx
AI3391 Artificial Intelligence Session 26 First order logic.pptxAI3391 Artificial Intelligence Session 26 First order logic.pptx
AI3391 Artificial Intelligence Session 26 First order logic.pptx
 

Recently uploaded

Fundamentals of Electric Drives and its applications.pptx
Fundamentals of Electric Drives and its applications.pptxFundamentals of Electric Drives and its applications.pptx
Fundamentals of Electric Drives and its applications.pptx
manasideore6
 
Water Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdfWater Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation & Control
 
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...
Amil Baba Dawood bangali
 
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
thanhdowork
 
Railway Signalling Principles Edition 3.pdf
Railway Signalling Principles Edition 3.pdfRailway Signalling Principles Edition 3.pdf
Railway Signalling Principles Edition 3.pdf
TeeVichai
 
HYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generationHYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generation
Robbie Edward Sayers
 
power quality voltage fluctuation UNIT - I.pptx
power quality voltage fluctuation UNIT - I.pptxpower quality voltage fluctuation UNIT - I.pptx
power quality voltage fluctuation UNIT - I.pptx
ViniHema
 
ASME IX(9) 2007 Full Version .pdf
ASME IX(9)  2007 Full Version       .pdfASME IX(9)  2007 Full Version       .pdf
ASME IX(9) 2007 Full Version .pdf
AhmedHussein950959
 
weather web application report.pdf
weather web application report.pdfweather web application report.pdf
weather web application report.pdf
Pratik Pawar
 
Immunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary AttacksImmunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary Attacks
gerogepatton
 
一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理
一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理
一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理
ydteq
 
Final project report on grocery store management system..pdf
Final project report on grocery store management system..pdfFinal project report on grocery store management system..pdf
Final project report on grocery store management system..pdf
Kamal Acharya
 
MCQ Soil mechanics questions (Soil shear strength).pdf
MCQ Soil mechanics questions (Soil shear strength).pdfMCQ Soil mechanics questions (Soil shear strength).pdf
MCQ Soil mechanics questions (Soil shear strength).pdf
Osamah Alsalih
 
H.Seo, ICLR 2024, MLILAB, KAIST AI.pdf
H.Seo,  ICLR 2024, MLILAB,  KAIST AI.pdfH.Seo,  ICLR 2024, MLILAB,  KAIST AI.pdf
H.Seo, ICLR 2024, MLILAB, KAIST AI.pdf
MLILAB
 
ethical hacking-mobile hacking methods.ppt
ethical hacking-mobile hacking methods.pptethical hacking-mobile hacking methods.ppt
ethical hacking-mobile hacking methods.ppt
Jayaprasanna4
 
Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&BDesign and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Sreedhar Chowdam
 
WATER CRISIS and its solutions-pptx 1234
WATER CRISIS and its solutions-pptx 1234WATER CRISIS and its solutions-pptx 1234
WATER CRISIS and its solutions-pptx 1234
AafreenAbuthahir2
 
road safety engineering r s e unit 3.pdf
road safety engineering  r s e unit 3.pdfroad safety engineering  r s e unit 3.pdf
road safety engineering r s e unit 3.pdf
VENKATESHvenky89705
 
space technology lecture notes on satellite
space technology lecture notes on satellitespace technology lecture notes on satellite
space technology lecture notes on satellite
ongomchris
 
block diagram and signal flow graph representation
block diagram and signal flow graph representationblock diagram and signal flow graph representation
block diagram and signal flow graph representation
Divya Somashekar
 

Recently uploaded (20)

Fundamentals of Electric Drives and its applications.pptx
Fundamentals of Electric Drives and its applications.pptxFundamentals of Electric Drives and its applications.pptx
Fundamentals of Electric Drives and its applications.pptx
 
Water Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdfWater Industry Process Automation and Control Monthly - May 2024.pdf
Water Industry Process Automation and Control Monthly - May 2024.pdf
 
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...
 
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Hori...
 
Railway Signalling Principles Edition 3.pdf
Railway Signalling Principles Edition 3.pdfRailway Signalling Principles Edition 3.pdf
Railway Signalling Principles Edition 3.pdf
 
HYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generationHYDROPOWER - Hydroelectric power generation
HYDROPOWER - Hydroelectric power generation
 
power quality voltage fluctuation UNIT - I.pptx
power quality voltage fluctuation UNIT - I.pptxpower quality voltage fluctuation UNIT - I.pptx
power quality voltage fluctuation UNIT - I.pptx
 
ASME IX(9) 2007 Full Version .pdf
ASME IX(9)  2007 Full Version       .pdfASME IX(9)  2007 Full Version       .pdf
ASME IX(9) 2007 Full Version .pdf
 
weather web application report.pdf
weather web application report.pdfweather web application report.pdf
weather web application report.pdf
 
Immunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary AttacksImmunizing Image Classifiers Against Localized Adversary Attacks
Immunizing Image Classifiers Against Localized Adversary Attacks
 
一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理
一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理
一比一原版(UofT毕业证)多伦多大学毕业证成绩单如何办理
 
Final project report on grocery store management system..pdf
Final project report on grocery store management system..pdfFinal project report on grocery store management system..pdf
Final project report on grocery store management system..pdf
 
MCQ Soil mechanics questions (Soil shear strength).pdf
MCQ Soil mechanics questions (Soil shear strength).pdfMCQ Soil mechanics questions (Soil shear strength).pdf
MCQ Soil mechanics questions (Soil shear strength).pdf
 
H.Seo, ICLR 2024, MLILAB, KAIST AI.pdf
H.Seo,  ICLR 2024, MLILAB,  KAIST AI.pdfH.Seo,  ICLR 2024, MLILAB,  KAIST AI.pdf
H.Seo, ICLR 2024, MLILAB, KAIST AI.pdf
 
ethical hacking-mobile hacking methods.ppt
ethical hacking-mobile hacking methods.pptethical hacking-mobile hacking methods.ppt
ethical hacking-mobile hacking methods.ppt
 
Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&BDesign and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
 
WATER CRISIS and its solutions-pptx 1234
WATER CRISIS and its solutions-pptx 1234WATER CRISIS and its solutions-pptx 1234
WATER CRISIS and its solutions-pptx 1234
 
road safety engineering r s e unit 3.pdf
road safety engineering  r s e unit 3.pdfroad safety engineering  r s e unit 3.pdf
road safety engineering r s e unit 3.pdf
 
space technology lecture notes on satellite
space technology lecture notes on satellitespace technology lecture notes on satellite
space technology lecture notes on satellite
 
block diagram and signal flow graph representation
block diagram and signal flow graph representationblock diagram and signal flow graph representation
block diagram and signal flow graph representation
 

AI_Session 18 Cryptoarithmetic problem.pptx

  • 1. ARTIFICAL INTELLIGENCE (R18 III(II Sem)) Department of computer science and engineering (AI/ML) Session 18 by Asst.Prof.M.Gokilavani VITS 4/25/2023 Dpaertment of CSE ( AL & ML) 1
  • 2. TEXTBOOK: • Artificial Intelligence A modern Approach, Third Edition, Stuart Russell and Peter Norvig, Pearson Education. REFERENCES: • Artificial Intelligence, 3rd Edn, E. Rich and K.Knight (TMH). • Artificial Intelligence, 3rd Edn, Patrick Henny Winston, Pearson Education. • Artificial Intelligence, Shivani Goel, Pearson Education. • Artificial Intelligence and Expert Systems- Patterson, Pearson Education. 4/25/2023 Dpaertment of CSE ( AL & ML) 2
  • 3. Topics covered in session 18 • Adversarial Search: Games, Optimal Decisions in Games, Alpha– Beta Pruning, Imperfect Real-Time Decisions. • Constraint Satisfaction Problems: Defining Constraint Satisfaction Problems, Constraint Propagation, Backtracking Search for CSPs, Local Search for CSPs, The Structure of Problems. • Propositional Logic: Knowledge-Based Agents, The Wumpus World, Logic, Propositional Logic, Propositional Theorem Proving: Inference and proofs, Proof by resolution, Horn clauses and definite clauses, Forward and backward chaining, Effective Propositional Model Checking, Agents Based on Propositional Logic. 4/25/2023 Dpaertment of CSE ( AL & ML) 3
  • 4. Cryptarithmetic Problem • Cryptarithmetic Problem is a type of constraint satisfaction problem where the game is about digits and its unique replacement either with alphabets or other symbols. • In cryptarithmetic problem, the digits (0-9) get substituted by some possible alphabets or symbols. • The task in cryptarithmetic problem is to substitute each digit with an alphabet to get the result arithmetically correct. • We can perform all the arithmetic operations on a given cryptarithmetic problem. 4/25/2023 4 Dpaertment of CSE ( AL & ML)
  • 5. Constraints for cryptarithmetic problem • Unique digit to be replaced with a unique alphabet (no repeated digits). • The result should satisfy the predefined arithmetic rules, i.e., 2+2 =4 • Digits should be from 0-9 only. • In addition operation only one carry forward. • The problem can be solved from both sides, i.e., lefthand side (L.H.S), or right-hand side (R.H.S) 4/25/2023 5 Dpaertment of CSE ( AL & ML)
  • 6. Example 1 • Given a cryptarithmetic problem, i.e., S E N D + M O R E = M O N E Y. 4/25/2023 6 Dpaertment of CSE ( AL & ML)
  • 7. 4/25/2023 Dpaertment of CSE ( AL & ML) 7
  • 8. Step 1 4/25/2023 8 Dpaertment of CSE ( AL & ML) • Starting from the left hand side (L.H.S) , the terms are S and M. Assign a digit which could give a satisfactory result. Let’s assign S->9 and M->1. Hence, we get a satisfactory result by adding up the terms and got an assignment for O as O->0 as well.
  • 9. Step 2 • Now, move ahead to the next terms E and O to get N as its output. 4/25/2023 9 Dpaertment of CSE ( AL & ML) Adding E and O, which means 5+0=0, which is not possible because we cannot assign the same digit to two letters.
  • 10. • Add carry 1 to the value E to change the value of alphabet. 4/25/2023 10 Dpaertment of CSE ( AL & ML)
  • 11. Step 3 4/25/2023 11 Dpaertment of CSE ( AL & ML) • Further, adding the next two terms N and R we get, But, we have already assigned E->5. Not possible with 5 to E Again, after solving the whole problem, we will get a carryover on this term, so our answer will be satisfied.
  • 12. Step 4 • Again, on adding the last two terms, i.e., the rightmost terms D and E, we get Y as its result. 4/25/2023 12 Dpaertment of CSE ( AL & ML)
  • 13. • Keeping all the constraints in mind, the final resultant is as follows: 4/25/2023 13 Dpaertment of CSE ( AL & ML) Alphabets Values S 9 E 5 N 6 D 7 M 1 O 0 R 8 Y 2
  • 16. Topics to be covered in next session 19 • Backtracking CSP’s Thank you!!! 4/25/2023 Dpaertment of CSE ( AL & ML) 16