SlideShare a Scribd company logo
VIJAYANANDA D MOHIRE
M.TECH SEM –III
REG. NO : 921DMTE0113
KSOU, MYSORE
DISSERATION PART – I :
DERIVING PROJECT-VALUES OF MULTI
AGENT SYSTEMS
1
PRESENTATION STRUCTURE
Aims & Objectives of this study
Research methodology
Project setup
Metrics, tools to be used
Expected outcomes from this study
Result presentation
Conclusions and Recommendations
2
AIMS OF THIS STUDY
Aim 1 : Identify current key issues in using MAS
Aim 2 : Identify & Evaluate value generated
by MAS based project
Aim 3 : Develop a general solution to
common issues faced in MAS project
3
OBJECTIVES OF THIS STUDY
Objective 1: To accomplish Aim 1, gather
literature related to issues faced
during MAS project development
Objective 2: To accomplish Aim 2, gather,Objective 2: To accomplish Aim 2, gather,
analyze and critically evaluate the
MAS project features
Objective 3: Explore Industry framework,
standards & best practices and
evaluate them to current scenario
4
RESEARCH METHODOLOGY
Research methodology 1:
To accomplish Objective 1, gather case
studies & Internet Surveys
Research methodology 2:Research methodology 2:
To accomplish Objective 2 &3, gather case
studies, Internet Surveys & conduct Action
research that involved self study and
deriving results
5
RESEARCH METHODOLOGY STEPS
Collecting data
Formulating a hypothesis or proposition
Testing the hypothesis
Interpreting resultsInterpreting results
Stating the conclusion
6
PROJECT DETAILS - LAYOUT
7
PROJECT DETAILS- EFFORT
PackagePackagePackagePackage EffortEffortEffortEffort estimates in daysestimates in daysestimates in daysestimates in days
1) Architecture 40
2) Behaviour 15
3) Ontology 15
4) Middleware 15
5) Testing 20
6) Development 60
TOTAL NO OF EFFORT DAYSTOTAL NO OF EFFORT DAYSTOTAL NO OF EFFORT DAYSTOTAL NO OF EFFORT DAYS 155155155155
8
PROJECT DETAILS- DATA STRUCTURE
9
PROJECT DETAILS-IMPLEMENTATION
10
PROJECT DETAILS-REPORTS
Sl.NoSl.NoSl.NoSl.No Report typeReport typeReport typeReport type Approximate Number ofApproximate Number ofApproximate Number ofApproximate Number of
reportsreportsreportsreports
1 User input, agent interaction 5
2 Design , modeling and project
SDLC related
5
3 Reports to demo project values 53 Reports to demo project values 5
4 Tools Installation setup,
Configuration and initial
parameters
5
5 Agent output , metrics collected,
debugging results
5
TOTAL REPORTSTOTAL REPORTSTOTAL REPORTSTOTAL REPORTS 25252525
11
PROJECT DETAILS-NW ARCH
12
PROJECT DETAILS-LOGICAL VIEW
13
PROJECT DETAILS- SECURITY
14
METRICS, TOOLS TO BE USED
Comparison unit /Comparison unit /Comparison unit /Comparison unit /
MetricsMetricsMetricsMetrics
Comparison unit /Comparison unit /Comparison unit /Comparison unit /
MetricsMetricsMetricsMetrics
Comparison unit /Comparison unit /Comparison unit /Comparison unit /
MetricsMetricsMetricsMetrics
1) Project metrics
like SDLC, Time,
cost of investment,
ROI,
3) Social, Proactive
behaviour and its
leverage into the projects
5) Closer to realism –
man machine
interactions, real world
scenariosROI,
Features benefits
etc
scenarios
2) Nature of control
and command like
– Autonomy,
Grained access
control, security
mechanism
4) Communication
protocols, modes of
operation, Centralised
and Decentralised ,
failure and recovery
mechanism
6) Problem solving skills-
how close it solves the
real problems and hard
problems
15
METRICS, TOOLS TO BE USED
Sl.NoSl.NoSl.NoSl.No Tools / SW applicationsTools / SW applicationsTools / SW applicationsTools / SW applications Purpose/ DetailsPurpose/ DetailsPurpose/ DetailsPurpose/ Details
1 Win Word 2007 editor For Documentation
2 Windows operating system Operating system
3 JRE/ JDK For Java environment
4 NetBeans Java IDE and Debugging4 NetBeans Java IDE and Debugging
5 JADE For Middleware and Hosting Java
Agents
6 Wintel System Laptop PC Hardware for deploying the application
16
EXPECTED OUTCOMES FROM THIS STUDY
Clear understanding of the prevailing current
issues in MAS development
Resolutions to the Research questions, Aims
and Objectives
Value creation by using suitable MASValue creation by using suitable MAS
techniques
Common solution to recurring issues in
project development for MAS
Reusable project artifacts and samples
17
RESULTS PRESENTATION
Comparison charts using comparable metrics
Project artifacts tables with Package level
comparison
Value proposition charts
Computation complexity statistics
Managerial KPIs
Process, Quality and Standards tables
Samples, Case studies, typical usage
Related formulas, references and statistics
18
CONCLUSIONS AND RECOMMENDATIONS
Main conclusion is that the current modes of
approaches to domestic Project development
lack the maturity as compared to scientific
community advances
A right approach to use the right tools and
techniques is needed specific to AI basedtechniques is needed specific to AI based
MAS projects
Recommend to leverage industry standards,
frameworks and policies and build a custom
model, resolving implementation issues
Derive and demonstrate true value of MAS
19

More Related Content

What's hot

Bilcare ltd
Bilcare ltdBilcare ltd
Bilcare ltd
Bilcare Research
 
Application retirement road_map_for_legacy_applications
Application retirement road_map_for_legacy_applicationsApplication retirement road_map_for_legacy_applications
Application retirement road_map_for_legacy_applications
Frank Morris
 
Service Mesh Talk for CTO Forum
Service Mesh Talk for CTO ForumService Mesh Talk for CTO Forum
Service Mesh Talk for CTO Forum
Rick Hightower
 
Optimize Data Connectivity in .NET Applications
Optimize Data Connectivity in .NET ApplicationsOptimize Data Connectivity in .NET Applications
Optimize Data Connectivity in .NET Applications
Abhishek Kant
 
Sutedjo - Digital Transformation for SAP
Sutedjo -  Digital Transformation for SAPSutedjo -  Digital Transformation for SAP
Sutedjo - Digital Transformation for SAP
PT Datacomm Diangraha
 
Aws based digital_transformation_platform
Aws based digital_transformation_platformAws based digital_transformation_platform
Aws based digital_transformation_platform
Slobodan Sipcic
 
flexpod_hadoop_cloudera
flexpod_hadoop_clouderaflexpod_hadoop_cloudera
flexpod_hadoop_cloudera
Prem Jain
 
Shrey_Kumar_Resume_01072016
Shrey_Kumar_Resume_01072016Shrey_Kumar_Resume_01072016
Shrey_Kumar_Resume_01072016
Shrey Kumar
 
Riverbed at Microsoft TechEd 2014
Riverbed at Microsoft TechEd 2014Riverbed at Microsoft TechEd 2014
Riverbed at Microsoft TechEd 2014
Riverbed Technology
 
AtLASpoint
AtLASpointAtLASpoint
AtLASpoint
Atlaspoint Pvt Ltd
 
Jan van der Vegt. Challenges faced with machine learning in practice
Jan van der Vegt. Challenges faced with machine learning in practiceJan van der Vegt. Challenges faced with machine learning in practice
Jan van der Vegt. Challenges faced with machine learning in practice
Lviv Startup Club
 
ABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG AxisbankABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG Axisbank
Abhijeet Ghag
 
Company Profile-iONE
Company Profile-iONECompany Profile-iONE
Company Profile-iONE
iONE ITSolutions
 
365 Data Centers Presentation for Businesses
365 Data Centers Presentation for Businesses365 Data Centers Presentation for Businesses
365 Data Centers Presentation for Businesses
365 Data Centers
 
January 2015 Webinar - Wins and Successes from 2014
January 2015 Webinar -  Wins and Successes from 2014January 2015 Webinar -  Wins and Successes from 2014
January 2015 Webinar - Wins and Successes from 2014
RapidScale
 
ETL Profile-Rajnish Kumar
ETL Profile-Rajnish KumarETL Profile-Rajnish Kumar
ETL Profile-Rajnish Kumar
Rajnish Kumar
 
Faster Data Processing for healthcare system
Faster Data Processing for healthcare systemFaster Data Processing for healthcare system
Faster Data Processing for healthcare system
Rolta
 
NetApp Clustered Data ONTAP with Oracle Databases
NetApp Clustered Data ONTAP with Oracle DatabasesNetApp Clustered Data ONTAP with Oracle Databases
NetApp Clustered Data ONTAP with Oracle Databases
NetApp
 
PLatzkeResume2014
PLatzkeResume2014PLatzkeResume2014
PLatzkeResume2014
Patricia Latzke
 
Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...
Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...
Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...
Infopulse
 

What's hot (20)

Bilcare ltd
Bilcare ltdBilcare ltd
Bilcare ltd
 
Application retirement road_map_for_legacy_applications
Application retirement road_map_for_legacy_applicationsApplication retirement road_map_for_legacy_applications
Application retirement road_map_for_legacy_applications
 
Service Mesh Talk for CTO Forum
Service Mesh Talk for CTO ForumService Mesh Talk for CTO Forum
Service Mesh Talk for CTO Forum
 
Optimize Data Connectivity in .NET Applications
Optimize Data Connectivity in .NET ApplicationsOptimize Data Connectivity in .NET Applications
Optimize Data Connectivity in .NET Applications
 
Sutedjo - Digital Transformation for SAP
Sutedjo -  Digital Transformation for SAPSutedjo -  Digital Transformation for SAP
Sutedjo - Digital Transformation for SAP
 
Aws based digital_transformation_platform
Aws based digital_transformation_platformAws based digital_transformation_platform
Aws based digital_transformation_platform
 
flexpod_hadoop_cloudera
flexpod_hadoop_clouderaflexpod_hadoop_cloudera
flexpod_hadoop_cloudera
 
Shrey_Kumar_Resume_01072016
Shrey_Kumar_Resume_01072016Shrey_Kumar_Resume_01072016
Shrey_Kumar_Resume_01072016
 
Riverbed at Microsoft TechEd 2014
Riverbed at Microsoft TechEd 2014Riverbed at Microsoft TechEd 2014
Riverbed at Microsoft TechEd 2014
 
AtLASpoint
AtLASpointAtLASpoint
AtLASpoint
 
Jan van der Vegt. Challenges faced with machine learning in practice
Jan van der Vegt. Challenges faced with machine learning in practiceJan van der Vegt. Challenges faced with machine learning in practice
Jan van der Vegt. Challenges faced with machine learning in practice
 
ABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG AxisbankABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG Axisbank
 
Company Profile-iONE
Company Profile-iONECompany Profile-iONE
Company Profile-iONE
 
365 Data Centers Presentation for Businesses
365 Data Centers Presentation for Businesses365 Data Centers Presentation for Businesses
365 Data Centers Presentation for Businesses
 
January 2015 Webinar - Wins and Successes from 2014
January 2015 Webinar -  Wins and Successes from 2014January 2015 Webinar -  Wins and Successes from 2014
January 2015 Webinar - Wins and Successes from 2014
 
ETL Profile-Rajnish Kumar
ETL Profile-Rajnish KumarETL Profile-Rajnish Kumar
ETL Profile-Rajnish Kumar
 
Faster Data Processing for healthcare system
Faster Data Processing for healthcare systemFaster Data Processing for healthcare system
Faster Data Processing for healthcare system
 
NetApp Clustered Data ONTAP with Oracle Databases
NetApp Clustered Data ONTAP with Oracle DatabasesNetApp Clustered Data ONTAP with Oracle Databases
NetApp Clustered Data ONTAP with Oracle Databases
 
PLatzkeResume2014
PLatzkeResume2014PLatzkeResume2014
PLatzkeResume2014
 
Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...
Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...
Intelligent, Efficient and Competitive Solutions for Your IT Operations High ...
 

Similar to MTech- Viva_Voce

PIACERE project overview, summary of objectives v2
PIACERE project overview, summary of objectives v2PIACERE project overview, summary of objectives v2
PIACERE project overview, summary of objectives v2
PIACERE
 
Bca 5th sem seminar(software measurements)
Bca 5th sem seminar(software measurements)Bca 5th sem seminar(software measurements)
Bca 5th sem seminar(software measurements)
MuskanSony
 
Ch07
Ch07Ch07
Presentation v4 print
Presentation v4 printPresentation v4 print
Presentation v4 print
Anna Malahova
 
Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...
Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...
Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...
RAKESH RANA
 
Software Productivity Framework
Software Productivity Framework Software Productivity Framework
Software Productivity Framework
Zinnov
 
Introduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.pptIntroduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.ppt
DrPreethiD1
 
Introduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).pptIntroduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).ppt
AbdugafforAbduganiye
 
Introduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.pptIntroduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.ppt
CIRMV1
 
Introduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).pptIntroduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).ppt
ManethPathirana
 
Introduction to Software Engineering ppt
Introduction to Software Engineering pptIntroduction to Software Engineering ppt
Introduction to Software Engineering ppt
dhruv04814902022
 
MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...
MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...
MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...
Tao Xie
 
Why is Test Driven Development for Analytics or Data Projects so Hard?
Why is Test Driven Development for Analytics or Data Projects so Hard?Why is Test Driven Development for Analytics or Data Projects so Hard?
Why is Test Driven Development for Analytics or Data Projects so Hard?
Phil Watt
 
Why is TDD so hard for Data Engineering and Analytics Projects?
Why is TDD so hard for Data Engineering and Analytics Projects?Why is TDD so hard for Data Engineering and Analytics Projects?
Why is TDD so hard for Data Engineering and Analytics Projects?
Phil Watt
 
CV_Vinay_Testing_QTP
CV_Vinay_Testing_QTP CV_Vinay_Testing_QTP
CV_Vinay_Testing_QTP
vinay123456
 
Meha_Ghadge
Meha_GhadgeMeha_Ghadge
Meha_Ghadge
Meha Ghadge
 
Measuring Productivity from Model-Based Development
Measuring Productivity from Model-Based DevelopmentMeasuring Productivity from Model-Based Development
Measuring Productivity from Model-Based Development
Juha-Pekka Tolvanen
 
Software Architecture Evaluation: A Systematic Mapping Study
Software Architecture Evaluation: A Systematic Mapping StudySoftware Architecture Evaluation: A Systematic Mapping Study
Software Architecture Evaluation: A Systematic Mapping Study
Sofia Ouhbi
 
SDLC Models and Their Implementation
SDLC Models and Their ImplementationSDLC Models and Their Implementation
SDLC Models and Their Implementation
Sonal Tiwari
 
IEEE 12207
IEEE 12207IEEE 12207
IEEE 12207
Joe Christensen
 

Similar to MTech- Viva_Voce (20)

PIACERE project overview, summary of objectives v2
PIACERE project overview, summary of objectives v2PIACERE project overview, summary of objectives v2
PIACERE project overview, summary of objectives v2
 
Bca 5th sem seminar(software measurements)
Bca 5th sem seminar(software measurements)Bca 5th sem seminar(software measurements)
Bca 5th sem seminar(software measurements)
 
Ch07
Ch07Ch07
Ch07
 
Presentation v4 print
Presentation v4 printPresentation v4 print
Presentation v4 print
 
Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...
Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...
Software Defect Prediction Techniques in the Automotive Domain: Evaluation, S...
 
Software Productivity Framework
Software Productivity Framework Software Productivity Framework
Software Productivity Framework
 
Introduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.pptIntroduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.ppt
 
Introduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).pptIntroduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).ppt
 
Introduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.pptIntroduction-to-Software-Engineering.ppt
Introduction-to-Software-Engineering.ppt
 
Introduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).pptIntroduction-to-Software-Engineering (1).ppt
Introduction-to-Software-Engineering (1).ppt
 
Introduction to Software Engineering ppt
Introduction to Software Engineering pptIntroduction to Software Engineering ppt
Introduction to Software Engineering ppt
 
MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...
MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...
MSR 2022 Foundational Contribution Award Talk: Software Analytics: Reflection...
 
Why is Test Driven Development for Analytics or Data Projects so Hard?
Why is Test Driven Development for Analytics or Data Projects so Hard?Why is Test Driven Development for Analytics or Data Projects so Hard?
Why is Test Driven Development for Analytics or Data Projects so Hard?
 
Why is TDD so hard for Data Engineering and Analytics Projects?
Why is TDD so hard for Data Engineering and Analytics Projects?Why is TDD so hard for Data Engineering and Analytics Projects?
Why is TDD so hard for Data Engineering and Analytics Projects?
 
CV_Vinay_Testing_QTP
CV_Vinay_Testing_QTP CV_Vinay_Testing_QTP
CV_Vinay_Testing_QTP
 
Meha_Ghadge
Meha_GhadgeMeha_Ghadge
Meha_Ghadge
 
Measuring Productivity from Model-Based Development
Measuring Productivity from Model-Based DevelopmentMeasuring Productivity from Model-Based Development
Measuring Productivity from Model-Based Development
 
Software Architecture Evaluation: A Systematic Mapping Study
Software Architecture Evaluation: A Systematic Mapping StudySoftware Architecture Evaluation: A Systematic Mapping Study
Software Architecture Evaluation: A Systematic Mapping Study
 
SDLC Models and Their Implementation
SDLC Models and Their ImplementationSDLC Models and Their Implementation
SDLC Models and Their Implementation
 
IEEE 12207
IEEE 12207IEEE 12207
IEEE 12207
 

More from Vijayananda Mohire

Quantum Algorithms for Electronics - IEEE Certificate
Quantum Algorithms for Electronics - IEEE CertificateQuantum Algorithms for Electronics - IEEE Certificate
Quantum Algorithms for Electronics - IEEE Certificate
Vijayananda Mohire
 
NexGen Solutions for cloud platforms, powered by GenQAI
NexGen Solutions for cloud platforms, powered by GenQAINexGen Solutions for cloud platforms, powered by GenQAI
NexGen Solutions for cloud platforms, powered by GenQAI
Vijayananda Mohire
 
Certificate- Peer Review of Book Chapter on ML
Certificate- Peer Review of Book Chapter on MLCertificate- Peer Review of Book Chapter on ML
Certificate- Peer Review of Book Chapter on ML
Vijayananda Mohire
 
Key projects Data Science and Engineering
Key projects Data Science and EngineeringKey projects Data Science and Engineering
Key projects Data Science and Engineering
Vijayananda Mohire
 
Key projects Data Science and Engineering
Key projects Data Science and EngineeringKey projects Data Science and Engineering
Key projects Data Science and Engineering
Vijayananda Mohire
 
Bhadale IT Hub-Multi Cloud and Multi QAI
Bhadale IT Hub-Multi Cloud and Multi QAIBhadale IT Hub-Multi Cloud and Multi QAI
Bhadale IT Hub-Multi Cloud and Multi QAI
Vijayananda Mohire
 
My key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAIMy key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAI
Vijayananda Mohire
 
Azure Quantum Workspace for developing Q# based quantum circuits
Azure Quantum Workspace for developing Q# based quantum circuitsAzure Quantum Workspace for developing Q# based quantum circuits
Azure Quantum Workspace for developing Q# based quantum circuits
Vijayananda Mohire
 
Key projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AIKey projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AI
Vijayananda Mohire
 
My Journey towards Artificial Intelligence
My Journey towards Artificial IntelligenceMy Journey towards Artificial Intelligence
My Journey towards Artificial Intelligence
Vijayananda Mohire
 
Bhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for AgricultureBhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for Agriculture
Vijayananda Mohire
 
Bhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for AgricultureBhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for Agriculture
Vijayananda Mohire
 
Bhadale IT Intel and Azure Cloud Offerings
Bhadale IT Intel and Azure Cloud OfferingsBhadale IT Intel and Azure Cloud Offerings
Bhadale IT Intel and Azure Cloud Offerings
Vijayananda Mohire
 
GitHub Copilot-vijaymohire
GitHub Copilot-vijaymohireGitHub Copilot-vijaymohire
GitHub Copilot-vijaymohire
Vijayananda Mohire
 
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical Implications
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical ImplicationsPractical ChatGPT From Use Cases to Prompt Engineering & Ethical Implications
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical Implications
Vijayananda Mohire
 
Cloud Infrastructure - Partner Delivery Accelerator (APAC)
Cloud Infrastructure - Partner Delivery Accelerator (APAC)Cloud Infrastructure - Partner Delivery Accelerator (APAC)
Cloud Infrastructure - Partner Delivery Accelerator (APAC)
Vijayananda Mohire
 
Red Hat Sales Specialist - Red Hat Enterprise Linux
Red Hat Sales Specialist - Red Hat Enterprise LinuxRed Hat Sales Specialist - Red Hat Enterprise Linux
Red Hat Sales Specialist - Red Hat Enterprise Linux
Vijayananda Mohire
 
RedHat_Transcript_Jan_2024
RedHat_Transcript_Jan_2024RedHat_Transcript_Jan_2024
RedHat_Transcript_Jan_2024
Vijayananda Mohire
 
Generative AI Business Transformation
Generative AI Business TransformationGenerative AI Business Transformation
Generative AI Business Transformation
Vijayananda Mohire
 
Microsoft Learn Transcript Jan 2024- vijaymohire
Microsoft Learn Transcript Jan 2024- vijaymohireMicrosoft Learn Transcript Jan 2024- vijaymohire
Microsoft Learn Transcript Jan 2024- vijaymohire
Vijayananda Mohire
 

More from Vijayananda Mohire (20)

Quantum Algorithms for Electronics - IEEE Certificate
Quantum Algorithms for Electronics - IEEE CertificateQuantum Algorithms for Electronics - IEEE Certificate
Quantum Algorithms for Electronics - IEEE Certificate
 
NexGen Solutions for cloud platforms, powered by GenQAI
NexGen Solutions for cloud platforms, powered by GenQAINexGen Solutions for cloud platforms, powered by GenQAI
NexGen Solutions for cloud platforms, powered by GenQAI
 
Certificate- Peer Review of Book Chapter on ML
Certificate- Peer Review of Book Chapter on MLCertificate- Peer Review of Book Chapter on ML
Certificate- Peer Review of Book Chapter on ML
 
Key projects Data Science and Engineering
Key projects Data Science and EngineeringKey projects Data Science and Engineering
Key projects Data Science and Engineering
 
Key projects Data Science and Engineering
Key projects Data Science and EngineeringKey projects Data Science and Engineering
Key projects Data Science and Engineering
 
Bhadale IT Hub-Multi Cloud and Multi QAI
Bhadale IT Hub-Multi Cloud and Multi QAIBhadale IT Hub-Multi Cloud and Multi QAI
Bhadale IT Hub-Multi Cloud and Multi QAI
 
My key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAIMy key hands-on projects in Quantum, and QAI
My key hands-on projects in Quantum, and QAI
 
Azure Quantum Workspace for developing Q# based quantum circuits
Azure Quantum Workspace for developing Q# based quantum circuitsAzure Quantum Workspace for developing Q# based quantum circuits
Azure Quantum Workspace for developing Q# based quantum circuits
 
Key projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AIKey projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AI
 
My Journey towards Artificial Intelligence
My Journey towards Artificial IntelligenceMy Journey towards Artificial Intelligence
My Journey towards Artificial Intelligence
 
Bhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for AgricultureBhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for Agriculture
 
Bhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for AgricultureBhadale IT Cloud Solutions for Agriculture
Bhadale IT Cloud Solutions for Agriculture
 
Bhadale IT Intel and Azure Cloud Offerings
Bhadale IT Intel and Azure Cloud OfferingsBhadale IT Intel and Azure Cloud Offerings
Bhadale IT Intel and Azure Cloud Offerings
 
GitHub Copilot-vijaymohire
GitHub Copilot-vijaymohireGitHub Copilot-vijaymohire
GitHub Copilot-vijaymohire
 
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical Implications
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical ImplicationsPractical ChatGPT From Use Cases to Prompt Engineering & Ethical Implications
Practical ChatGPT From Use Cases to Prompt Engineering & Ethical Implications
 
Cloud Infrastructure - Partner Delivery Accelerator (APAC)
Cloud Infrastructure - Partner Delivery Accelerator (APAC)Cloud Infrastructure - Partner Delivery Accelerator (APAC)
Cloud Infrastructure - Partner Delivery Accelerator (APAC)
 
Red Hat Sales Specialist - Red Hat Enterprise Linux
Red Hat Sales Specialist - Red Hat Enterprise LinuxRed Hat Sales Specialist - Red Hat Enterprise Linux
Red Hat Sales Specialist - Red Hat Enterprise Linux
 
RedHat_Transcript_Jan_2024
RedHat_Transcript_Jan_2024RedHat_Transcript_Jan_2024
RedHat_Transcript_Jan_2024
 
Generative AI Business Transformation
Generative AI Business TransformationGenerative AI Business Transformation
Generative AI Business Transformation
 
Microsoft Learn Transcript Jan 2024- vijaymohire
Microsoft Learn Transcript Jan 2024- vijaymohireMicrosoft Learn Transcript Jan 2024- vijaymohire
Microsoft Learn Transcript Jan 2024- vijaymohire
 

Recently uploaded

Liberal Approach to the Study of Indian Politics.pdf
Liberal Approach to the Study of Indian Politics.pdfLiberal Approach to the Study of Indian Politics.pdf
Liberal Approach to the Study of Indian Politics.pdf
WaniBasim
 
Film vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movieFilm vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movie
Nicholas Montgomery
 
Hindi varnamala | hindi alphabet PPT.pdf
Hindi varnamala | hindi alphabet PPT.pdfHindi varnamala | hindi alphabet PPT.pdf
Hindi varnamala | hindi alphabet PPT.pdf
Dr. Mulla Adam Ali
 
How to Create a More Engaging and Human Online Learning Experience
How to Create a More Engaging and Human Online Learning Experience How to Create a More Engaging and Human Online Learning Experience
How to Create a More Engaging and Human Online Learning Experience
Wahiba Chair Training & Consulting
 
writing about opinions about Australia the movie
writing about opinions about Australia the moviewriting about opinions about Australia the movie
writing about opinions about Australia the movie
Nicholas Montgomery
 
Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47
MysoreMuleSoftMeetup
 
Leveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit InnovationLeveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit Innovation
TechSoup
 
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
GeorgeMilliken2
 
A Independência da América Espanhola LAPBOOK.pdf
A Independência da América Espanhola LAPBOOK.pdfA Independência da América Espanhola LAPBOOK.pdf
A Independência da América Espanhola LAPBOOK.pdf
Jean Carlos Nunes Paixão
 
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
imrankhan141184
 
IGCSE Biology Chapter 14- Reproduction in Plants.pdf
IGCSE Biology Chapter 14- Reproduction in Plants.pdfIGCSE Biology Chapter 14- Reproduction in Plants.pdf
IGCSE Biology Chapter 14- Reproduction in Plants.pdf
Amin Marwan
 
C1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptx
C1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptxC1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptx
C1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptx
mulvey2
 
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdfANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
Priyankaranawat4
 
clinical examination of hip joint (1).pdf
clinical examination of hip joint (1).pdfclinical examination of hip joint (1).pdf
clinical examination of hip joint (1).pdf
Priyankaranawat4
 
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skillsspot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
haiqairshad
 
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
Nguyen Thanh Tu Collection
 
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
PECB
 
The History of Stoke Newington Street Names
The History of Stoke Newington Street NamesThe History of Stoke Newington Street Names
The History of Stoke Newington Street Names
History of Stoke Newington
 
বাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdf
বাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdfবাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdf
বাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdf
eBook.com.bd (প্রয়োজনীয় বাংলা বই)
 
The basics of sentences session 6pptx.pptx
The basics of sentences session 6pptx.pptxThe basics of sentences session 6pptx.pptx
The basics of sentences session 6pptx.pptx
heathfieldcps1
 

Recently uploaded (20)

Liberal Approach to the Study of Indian Politics.pdf
Liberal Approach to the Study of Indian Politics.pdfLiberal Approach to the Study of Indian Politics.pdf
Liberal Approach to the Study of Indian Politics.pdf
 
Film vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movieFilm vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movie
 
Hindi varnamala | hindi alphabet PPT.pdf
Hindi varnamala | hindi alphabet PPT.pdfHindi varnamala | hindi alphabet PPT.pdf
Hindi varnamala | hindi alphabet PPT.pdf
 
How to Create a More Engaging and Human Online Learning Experience
How to Create a More Engaging and Human Online Learning Experience How to Create a More Engaging and Human Online Learning Experience
How to Create a More Engaging and Human Online Learning Experience
 
writing about opinions about Australia the movie
writing about opinions about Australia the moviewriting about opinions about Australia the movie
writing about opinions about Australia the movie
 
Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47Mule event processing models | MuleSoft Mysore Meetup #47
Mule event processing models | MuleSoft Mysore Meetup #47
 
Leveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit InnovationLeveraging Generative AI to Drive Nonprofit Innovation
Leveraging Generative AI to Drive Nonprofit Innovation
 
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
 
A Independência da América Espanhola LAPBOOK.pdf
A Independência da América Espanhola LAPBOOK.pdfA Independência da América Espanhola LAPBOOK.pdf
A Independência da América Espanhola LAPBOOK.pdf
 
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
Traditional Musical Instruments of Arunachal Pradesh and Uttar Pradesh - RAYH...
 
IGCSE Biology Chapter 14- Reproduction in Plants.pdf
IGCSE Biology Chapter 14- Reproduction in Plants.pdfIGCSE Biology Chapter 14- Reproduction in Plants.pdf
IGCSE Biology Chapter 14- Reproduction in Plants.pdf
 
C1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptx
C1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptxC1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptx
C1 Rubenstein AP HuG xxxxxxxxxxxxxx.pptx
 
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdfANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
 
clinical examination of hip joint (1).pdf
clinical examination of hip joint (1).pdfclinical examination of hip joint (1).pdf
clinical examination of hip joint (1).pdf
 
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skillsspot a liar (Haiqa 146).pptx Technical writhing and presentation skills
spot a liar (Haiqa 146).pptx Technical writhing and presentation skills
 
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
 
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
 
The History of Stoke Newington Street Names
The History of Stoke Newington Street NamesThe History of Stoke Newington Street Names
The History of Stoke Newington Street Names
 
বাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdf
বাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdfবাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdf
বাংলাদেশ অর্থনৈতিক সমীক্ষা (Economic Review) ২০২৪ UJS App.pdf
 
The basics of sentences session 6pptx.pptx
The basics of sentences session 6pptx.pptxThe basics of sentences session 6pptx.pptx
The basics of sentences session 6pptx.pptx
 

MTech- Viva_Voce

  • 1. VIJAYANANDA D MOHIRE M.TECH SEM –III REG. NO : 921DMTE0113 KSOU, MYSORE DISSERATION PART – I : DERIVING PROJECT-VALUES OF MULTI AGENT SYSTEMS 1
  • 2. PRESENTATION STRUCTURE Aims & Objectives of this study Research methodology Project setup Metrics, tools to be used Expected outcomes from this study Result presentation Conclusions and Recommendations 2
  • 3. AIMS OF THIS STUDY Aim 1 : Identify current key issues in using MAS Aim 2 : Identify & Evaluate value generated by MAS based project Aim 3 : Develop a general solution to common issues faced in MAS project 3
  • 4. OBJECTIVES OF THIS STUDY Objective 1: To accomplish Aim 1, gather literature related to issues faced during MAS project development Objective 2: To accomplish Aim 2, gather,Objective 2: To accomplish Aim 2, gather, analyze and critically evaluate the MAS project features Objective 3: Explore Industry framework, standards & best practices and evaluate them to current scenario 4
  • 5. RESEARCH METHODOLOGY Research methodology 1: To accomplish Objective 1, gather case studies & Internet Surveys Research methodology 2:Research methodology 2: To accomplish Objective 2 &3, gather case studies, Internet Surveys & conduct Action research that involved self study and deriving results 5
  • 6. RESEARCH METHODOLOGY STEPS Collecting data Formulating a hypothesis or proposition Testing the hypothesis Interpreting resultsInterpreting results Stating the conclusion 6
  • 7. PROJECT DETAILS - LAYOUT 7
  • 8. PROJECT DETAILS- EFFORT PackagePackagePackagePackage EffortEffortEffortEffort estimates in daysestimates in daysestimates in daysestimates in days 1) Architecture 40 2) Behaviour 15 3) Ontology 15 4) Middleware 15 5) Testing 20 6) Development 60 TOTAL NO OF EFFORT DAYSTOTAL NO OF EFFORT DAYSTOTAL NO OF EFFORT DAYSTOTAL NO OF EFFORT DAYS 155155155155 8
  • 9. PROJECT DETAILS- DATA STRUCTURE 9
  • 11. PROJECT DETAILS-REPORTS Sl.NoSl.NoSl.NoSl.No Report typeReport typeReport typeReport type Approximate Number ofApproximate Number ofApproximate Number ofApproximate Number of reportsreportsreportsreports 1 User input, agent interaction 5 2 Design , modeling and project SDLC related 5 3 Reports to demo project values 53 Reports to demo project values 5 4 Tools Installation setup, Configuration and initial parameters 5 5 Agent output , metrics collected, debugging results 5 TOTAL REPORTSTOTAL REPORTSTOTAL REPORTSTOTAL REPORTS 25252525 11
  • 15. METRICS, TOOLS TO BE USED Comparison unit /Comparison unit /Comparison unit /Comparison unit / MetricsMetricsMetricsMetrics Comparison unit /Comparison unit /Comparison unit /Comparison unit / MetricsMetricsMetricsMetrics Comparison unit /Comparison unit /Comparison unit /Comparison unit / MetricsMetricsMetricsMetrics 1) Project metrics like SDLC, Time, cost of investment, ROI, 3) Social, Proactive behaviour and its leverage into the projects 5) Closer to realism – man machine interactions, real world scenariosROI, Features benefits etc scenarios 2) Nature of control and command like – Autonomy, Grained access control, security mechanism 4) Communication protocols, modes of operation, Centralised and Decentralised , failure and recovery mechanism 6) Problem solving skills- how close it solves the real problems and hard problems 15
  • 16. METRICS, TOOLS TO BE USED Sl.NoSl.NoSl.NoSl.No Tools / SW applicationsTools / SW applicationsTools / SW applicationsTools / SW applications Purpose/ DetailsPurpose/ DetailsPurpose/ DetailsPurpose/ Details 1 Win Word 2007 editor For Documentation 2 Windows operating system Operating system 3 JRE/ JDK For Java environment 4 NetBeans Java IDE and Debugging4 NetBeans Java IDE and Debugging 5 JADE For Middleware and Hosting Java Agents 6 Wintel System Laptop PC Hardware for deploying the application 16
  • 17. EXPECTED OUTCOMES FROM THIS STUDY Clear understanding of the prevailing current issues in MAS development Resolutions to the Research questions, Aims and Objectives Value creation by using suitable MASValue creation by using suitable MAS techniques Common solution to recurring issues in project development for MAS Reusable project artifacts and samples 17
  • 18. RESULTS PRESENTATION Comparison charts using comparable metrics Project artifacts tables with Package level comparison Value proposition charts Computation complexity statistics Managerial KPIs Process, Quality and Standards tables Samples, Case studies, typical usage Related formulas, references and statistics 18
  • 19. CONCLUSIONS AND RECOMMENDATIONS Main conclusion is that the current modes of approaches to domestic Project development lack the maturity as compared to scientific community advances A right approach to use the right tools and techniques is needed specific to AI basedtechniques is needed specific to AI based MAS projects Recommend to leverage industry standards, frameworks and policies and build a custom model, resolving implementation issues Derive and demonstrate true value of MAS 19