SlideShare a Scribd company logo
DYNAMICDYNAMIC
PROGRAMMIPROGRAMMI
NGNG
Name: MD.Mojibul
Hoque
Roll: 504
Registration: WUB
3/10/23/504
DYNAMIC PROGRAMMING
 Dynamic Programming is an algorithm design
technique for optimization problems: often
minimizing or maximizing.
 Like divide and conquer, DP solves problems by
combining solutions to sub-problems.
 Unlike divide and conquer, sub-problems are not
independent.
 Sub-problems may share sub-sub-problems,
DYNAMIC PROGRAMMING
 The term Dynamic Programming comes from
Control Theory, not computer science.
Programming refers to the use of tables (arrays)
to construct a solution.
 In dynamic programming we usually reduce time
by increasing the amount of space
 We solve the problem by solving sub-problems of
increasing size and saving each optimal solution
in a table (usually).
 The table is then used for finding the optimal
solution to larger problems.
 Time is saved since each sub-problem is solved
only once.

More Related Content

Viewers also liked

[ACM-ICPC] 0 - ACM-ICPC
[ACM-ICPC] 0 - ACM-ICPC[ACM-ICPC] 0 - ACM-ICPC
[ACM-ICPC] 0 - ACM-ICPCChih-Hsuan Kuo
 
[ACM-ICPC] Top-down & Bottom-up
[ACM-ICPC] Top-down & Bottom-up[ACM-ICPC] Top-down & Bottom-up
[ACM-ICPC] Top-down & Bottom-upChih-Hsuan Kuo
 
ACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems Review
ACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems ReviewACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems Review
ACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems Review
Roman Elizarov
 
[ACM-ICPC] Bipartite Matching
[ACM-ICPC] Bipartite Matching[ACM-ICPC] Bipartite Matching
[ACM-ICPC] Bipartite Matching
Chih-Hsuan Kuo
 
[ACM-ICPC] Efficient Algorithm
[ACM-ICPC] Efficient Algorithm[ACM-ICPC] Efficient Algorithm
[ACM-ICPC] Efficient AlgorithmChih-Hsuan Kuo
 
[ACM-ICPC] Minimum Cut
[ACM-ICPC] Minimum Cut[ACM-ICPC] Minimum Cut
[ACM-ICPC] Minimum Cut
Chih-Hsuan Kuo
 
[ACM-ICPC] Traversal
[ACM-ICPC] Traversal[ACM-ICPC] Traversal
[ACM-ICPC] Traversal
Chih-Hsuan Kuo
 
Effective Modern C++ - Item 35 & 36
Effective Modern C++ - Item 35 & 36Effective Modern C++ - Item 35 & 36
Effective Modern C++ - Item 35 & 36
Chih-Hsuan Kuo
 
[ACM-ICPC] Binary Search
[ACM-ICPC] Binary Search[ACM-ICPC] Binary Search
[ACM-ICPC] Binary Search
陳 鵬宇
 
[ACM-ICPC] Greedy Algorithm
[ACM-ICPC] Greedy Algorithm[ACM-ICPC] Greedy Algorithm
[ACM-ICPC] Greedy Algorithm
陳 鵬宇
 
在開始工作以前,我以為我會寫扣。
在開始工作以前,我以為我會寫扣。在開始工作以前,我以為我會寫扣。
在開始工作以前,我以為我會寫扣。
Chih-Hsuan Kuo
 
Lafontaine_Alexandre_2016_Thesis
Lafontaine_Alexandre_2016_ThesisLafontaine_Alexandre_2016_Thesis
Lafontaine_Alexandre_2016_Thesis
Alexandre Lafontaine
 
Preventing_Cuts_certificate
Preventing_Cuts_certificatePreventing_Cuts_certificate
Preventing_Cuts_certificate
Shona Marupo
 
Tp tics
Tp ticsTp tics
Tp tics
Gabuchiii
 
La Robótica. El CHAUX
La Robótica. El CHAUXLa Robótica. El CHAUX
La Robótica. El CHAUX
Cristian Salazar el CHAUX
 
Lição 5
Lição 5Lição 5
Lição 5
Marilene Valente
 
Examen
ExamenExamen
Tanu_Dewan_eTOM
Tanu_Dewan_eTOMTanu_Dewan_eTOM
Tanu_Dewan_eTOM
Tanu Dewan
 
Az uvegtol az aranyig2
Az uvegtol az aranyig2Az uvegtol az aranyig2
Az uvegtol az aranyig2
Agnes Tip
 
Sonsda nova tie correto
Sonsda nova tie corretoSonsda nova tie correto
Sonsda nova tie correto
Meio & Mensagem
 

Viewers also liked (20)

[ACM-ICPC] 0 - ACM-ICPC
[ACM-ICPC] 0 - ACM-ICPC[ACM-ICPC] 0 - ACM-ICPC
[ACM-ICPC] 0 - ACM-ICPC
 
[ACM-ICPC] Top-down & Bottom-up
[ACM-ICPC] Top-down & Bottom-up[ACM-ICPC] Top-down & Bottom-up
[ACM-ICPC] Top-down & Bottom-up
 
ACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems Review
ACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems ReviewACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems Review
ACM ICPC 2013 NEERC (Northeastern European Regional Contest) Problems Review
 
[ACM-ICPC] Bipartite Matching
[ACM-ICPC] Bipartite Matching[ACM-ICPC] Bipartite Matching
[ACM-ICPC] Bipartite Matching
 
[ACM-ICPC] Efficient Algorithm
[ACM-ICPC] Efficient Algorithm[ACM-ICPC] Efficient Algorithm
[ACM-ICPC] Efficient Algorithm
 
[ACM-ICPC] Minimum Cut
[ACM-ICPC] Minimum Cut[ACM-ICPC] Minimum Cut
[ACM-ICPC] Minimum Cut
 
[ACM-ICPC] Traversal
[ACM-ICPC] Traversal[ACM-ICPC] Traversal
[ACM-ICPC] Traversal
 
Effective Modern C++ - Item 35 & 36
Effective Modern C++ - Item 35 & 36Effective Modern C++ - Item 35 & 36
Effective Modern C++ - Item 35 & 36
 
[ACM-ICPC] Binary Search
[ACM-ICPC] Binary Search[ACM-ICPC] Binary Search
[ACM-ICPC] Binary Search
 
[ACM-ICPC] Greedy Algorithm
[ACM-ICPC] Greedy Algorithm[ACM-ICPC] Greedy Algorithm
[ACM-ICPC] Greedy Algorithm
 
在開始工作以前,我以為我會寫扣。
在開始工作以前,我以為我會寫扣。在開始工作以前,我以為我會寫扣。
在開始工作以前,我以為我會寫扣。
 
Lafontaine_Alexandre_2016_Thesis
Lafontaine_Alexandre_2016_ThesisLafontaine_Alexandre_2016_Thesis
Lafontaine_Alexandre_2016_Thesis
 
Preventing_Cuts_certificate
Preventing_Cuts_certificatePreventing_Cuts_certificate
Preventing_Cuts_certificate
 
Tp tics
Tp ticsTp tics
Tp tics
 
La Robótica. El CHAUX
La Robótica. El CHAUXLa Robótica. El CHAUX
La Robótica. El CHAUX
 
Lição 5
Lição 5Lição 5
Lição 5
 
Examen
ExamenExamen
Examen
 
Tanu_Dewan_eTOM
Tanu_Dewan_eTOMTanu_Dewan_eTOM
Tanu_Dewan_eTOM
 
Az uvegtol az aranyig2
Az uvegtol az aranyig2Az uvegtol az aranyig2
Az uvegtol az aranyig2
 
Sonsda nova tie correto
Sonsda nova tie corretoSonsda nova tie correto
Sonsda nova tie correto
 

Similar to Dynamic programming

Introduction to Dynamic Programming, Principle of Optimality
Introduction to Dynamic Programming, Principle of OptimalityIntroduction to Dynamic Programming, Principle of Optimality
Introduction to Dynamic Programming, Principle of Optimality
Bhavin Darji
 
Dynamic Programing.pptx good for understanding
Dynamic Programing.pptx good for understandingDynamic Programing.pptx good for understanding
Dynamic Programing.pptx good for understanding
HUSNAINAHMAD39
 
ADA Unit 2.pptx
ADA Unit 2.pptxADA Unit 2.pptx
ADA Unit 2.pptx
AmanKumar879992
 
Introduction to dynamic programming
Introduction to dynamic programmingIntroduction to dynamic programming
Introduction to dynamic programming
Amisha Narsingani
 
Pintu ram
Pintu ramPintu ram
Pintu ram
pinturam2
 
Module 2ppt.pptx divid and conquer method
Module 2ppt.pptx divid and conquer methodModule 2ppt.pptx divid and conquer method
Module 2ppt.pptx divid and conquer method
JyoReddy9
 
Algorithm1
Algorithm1Algorithm1
Algorithm1
Emran Nur
 
Algorithm1
Algorithm1Algorithm1
Algorithm1
emran nur
 
Divide and conquer algorithm
Divide and conquer algorithmDivide and conquer algorithm
Divide and conquer algorithm
CHANDAN KUMAR
 
Top down design
Top down designTop down design
Top down design
Chaffey College
 
Dynamic programming, Branch and bound algorithm & Greedy algorithms
Dynamic programming, Branch and bound algorithm & Greedy algorithms Dynamic programming, Branch and bound algorithm & Greedy algorithms
Dynamic programming, Branch and bound algorithm & Greedy algorithms
SURBHI SAROHA
 
Algorithms Design Patterns
Algorithms Design PatternsAlgorithms Design Patterns
Algorithms Design Patterns
Ashwin Shiv
 
Dynamic programming 2
Dynamic programming 2Dynamic programming 2
Dynamic programming 2
Roy Thomas
 
Dynamic Programming.pptx
Dynamic Programming.pptxDynamic Programming.pptx
Dynamic Programming.pptx
MuktarHossain13
 
Dynamic Programming
Dynamic ProgrammingDynamic Programming
Dynamic Programming
Bharat Bhushan
 
Algorithm Design Technique
Algorithm Design Technique Algorithm Design Technique
Algorithm Design Technique
Bharat Bhushan
 
3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx
3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx
3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx
Agoyi1
 
csce411-set7.ppt
csce411-set7.pptcsce411-set7.ppt
csce411-set7.ppt
JoshCasas1
 
Session 3 : Competitive programming 1
Session 3 : Competitive programming 1Session 3 : Competitive programming 1
Session 3 : Competitive programming 1
Koderunners
 
DP Project Report
DP Project ReportDP Project Report
DP Project Report
Chawal Ukesh
 

Similar to Dynamic programming (20)

Introduction to Dynamic Programming, Principle of Optimality
Introduction to Dynamic Programming, Principle of OptimalityIntroduction to Dynamic Programming, Principle of Optimality
Introduction to Dynamic Programming, Principle of Optimality
 
Dynamic Programing.pptx good for understanding
Dynamic Programing.pptx good for understandingDynamic Programing.pptx good for understanding
Dynamic Programing.pptx good for understanding
 
ADA Unit 2.pptx
ADA Unit 2.pptxADA Unit 2.pptx
ADA Unit 2.pptx
 
Introduction to dynamic programming
Introduction to dynamic programmingIntroduction to dynamic programming
Introduction to dynamic programming
 
Pintu ram
Pintu ramPintu ram
Pintu ram
 
Module 2ppt.pptx divid and conquer method
Module 2ppt.pptx divid and conquer methodModule 2ppt.pptx divid and conquer method
Module 2ppt.pptx divid and conquer method
 
Algorithm1
Algorithm1Algorithm1
Algorithm1
 
Algorithm1
Algorithm1Algorithm1
Algorithm1
 
Divide and conquer algorithm
Divide and conquer algorithmDivide and conquer algorithm
Divide and conquer algorithm
 
Top down design
Top down designTop down design
Top down design
 
Dynamic programming, Branch and bound algorithm & Greedy algorithms
Dynamic programming, Branch and bound algorithm & Greedy algorithms Dynamic programming, Branch and bound algorithm & Greedy algorithms
Dynamic programming, Branch and bound algorithm & Greedy algorithms
 
Algorithms Design Patterns
Algorithms Design PatternsAlgorithms Design Patterns
Algorithms Design Patterns
 
Dynamic programming 2
Dynamic programming 2Dynamic programming 2
Dynamic programming 2
 
Dynamic Programming.pptx
Dynamic Programming.pptxDynamic Programming.pptx
Dynamic Programming.pptx
 
Dynamic Programming
Dynamic ProgrammingDynamic Programming
Dynamic Programming
 
Algorithm Design Technique
Algorithm Design Technique Algorithm Design Technique
Algorithm Design Technique
 
3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx
3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx
3. CPT121 - Introduction to Problem Solving - Module 1 - Unit 3.pptx
 
csce411-set7.ppt
csce411-set7.pptcsce411-set7.ppt
csce411-set7.ppt
 
Session 3 : Competitive programming 1
Session 3 : Competitive programming 1Session 3 : Competitive programming 1
Session 3 : Competitive programming 1
 
DP Project Report
DP Project ReportDP Project Report
DP Project Report
 

More from Md.Mojibul Hoque

Facebook Marketing
Facebook Marketing Facebook Marketing
Facebook Marketing
Md.Mojibul Hoque
 
Surela
SurelaSurela
Harvard University database
Harvard University databaseHarvard University database
Harvard University database
Md.Mojibul Hoque
 
Business level strategy
Business level strategyBusiness level strategy
Business level strategy
Md.Mojibul Hoque
 
Establishing objectives
Establishing objectivesEstablishing objectives
Establishing objectives
Md.Mojibul Hoque
 
Value chain and SWOT analysis
Value chain and SWOT analysisValue chain and SWOT analysis
Value chain and SWOT analysis
Md.Mojibul Hoque
 
Ms sql-server
Ms sql-serverMs sql-server
Ms sql-server
Md.Mojibul Hoque
 
University Student Payment System ( USPS )
University Student Payment System ( USPS )University Student Payment System ( USPS )
University Student Payment System ( USPS )
Md.Mojibul Hoque
 
Code smells and remedies
Code smells and remediesCode smells and remedies
Code smells and remedies
Md.Mojibul Hoque
 
Software design principles
Software design principlesSoftware design principles
Software design principles
Md.Mojibul Hoque
 
Writing a research report
Writing a research reportWriting a research report
Writing a research report
Md.Mojibul Hoque
 

More from Md.Mojibul Hoque (11)

Facebook Marketing
Facebook Marketing Facebook Marketing
Facebook Marketing
 
Surela
SurelaSurela
Surela
 
Harvard University database
Harvard University databaseHarvard University database
Harvard University database
 
Business level strategy
Business level strategyBusiness level strategy
Business level strategy
 
Establishing objectives
Establishing objectivesEstablishing objectives
Establishing objectives
 
Value chain and SWOT analysis
Value chain and SWOT analysisValue chain and SWOT analysis
Value chain and SWOT analysis
 
Ms sql-server
Ms sql-serverMs sql-server
Ms sql-server
 
University Student Payment System ( USPS )
University Student Payment System ( USPS )University Student Payment System ( USPS )
University Student Payment System ( USPS )
 
Code smells and remedies
Code smells and remediesCode smells and remedies
Code smells and remedies
 
Software design principles
Software design principlesSoftware design principles
Software design principles
 
Writing a research report
Writing a research reportWriting a research report
Writing a research report
 

Recently uploaded

UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
DianaGray10
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Neo4j
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
Adtran
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
DianaGray10
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
panagenda
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
Alpen-Adria-Universität
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Speck&Tech
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Safe Software
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
Daiki Mogmet Ito
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
Aftab Hussain
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
Edge AI and Vision Alliance
 
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing DaysClimate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Kari Kakkonen
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
DianaGray10
 

Recently uploaded (20)

UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
 
Removing Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software FuzzingRemoving Uninteresting Bytes in Software Fuzzing
Removing Uninteresting Bytes in Software Fuzzing
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
 
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing DaysClimate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
 

Dynamic programming

  • 2. DYNAMIC PROGRAMMING  Dynamic Programming is an algorithm design technique for optimization problems: often minimizing or maximizing.  Like divide and conquer, DP solves problems by combining solutions to sub-problems.  Unlike divide and conquer, sub-problems are not independent.  Sub-problems may share sub-sub-problems,
  • 3. DYNAMIC PROGRAMMING  The term Dynamic Programming comes from Control Theory, not computer science. Programming refers to the use of tables (arrays) to construct a solution.  In dynamic programming we usually reduce time by increasing the amount of space  We solve the problem by solving sub-problems of increasing size and saving each optimal solution in a table (usually).  The table is then used for finding the optimal solution to larger problems.  Time is saved since each sub-problem is solved only once.