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Dr. Priti Srinivas Sajja

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1 Dr. Priti Srinivas Sajja
Lecture for the State level seminar organized by Shri H. J. Doshi Information Technology Institute, Jamnagar Software Engineering Dr. Priti Srinivas Sajja Associate Professor G H Patel P G Department of Computer Science and Technology Sardar Patel University, Vallabh Vidyanagar , Gujarat Created By Dr. Priti Srinivas Sajja

2 Introduction and Contact Information Name: Dr Priti Srinivas Sajja Communication: Mobile : URL: Academic qualifications : Ph. D in Computer Science Thesis title: Knowledge-Based Systems for Socio- Economic Development Subject area of specialization : Artificial Intelligence Publications : 84 in International/ National Conferences, Journals & Books Academic position : Associate Professor Department of Computer Science Sardar Patel University Vallabh Vidyanagar

3 Agent Oriented Software Engineering
Lecture Plan Software Engineering Architectures Waterfall Spiral Iterative and Prototype RAD Model for KBS development Agents Introduction Typologies Multi Agent Systems Framework Communication between Agents Examples of System Designs using Agents E-Learning Agent Based Systems Multi layer KBS KGrid LOR –Layered Agents Approach

4 Software and Software Engineering
Software engineering is a modeling activity. Software engineering activity is a problem solving activity. Software engineering is a knowledge acquisition activity. Software engineering is a rationale driven activity. Software is a bundle of data, data structure, comments and instructions. Data Data Structures Instruction Comments Software Development can be carried out in ad hoc manner or systematic way (bigger project).

5 Example Instruction Data Structure Data Comments Push A
Push: Method on Stack S Data Structure Data A: Primitive Data Structure (Integer) Stack : Say S -Data Structure Push A //pushes an integer A to stack S Value A //pushes…Comments Comments

6 that represents the highest level of abstraction.
SE Architectures A process consisting of all the necessary activities for developing a software system that represents the highest level of abstraction. Popular Architectures are: Waterfall Spiral Iterative and Prototype Rapid Application Development …..

7 Typical SE Activities Project proposal Portfolio management
Requirement gathering Anticipation (mixed blessings) Investigation (fact finding methods) and Specification (decision tree, table and structured English) Feasibility Studies Economical Technical Operational Logical Design (DFD/UML ) Physical Design Design of output Design of input Design of databases, processes, data flows, control, run time procedure, security, etc. Coding Testing and Certification Training, Implementation, Evaluation Typical SE Activities

8 Requirement Acquisition
All requirements must be known. Deliverables created for each phase are considered frozen – less flexibility. Can give a false impression of progress. Not iterative. Integration at the end. Little opportunity for customer to preview the system. Waterfall Model Requirement Acquisition V & V Design Implementation Verification Maintenance Requirements When to use? Requirements are very well known. Product definition is stable. Technology is understood. New version of an existing product. Porting an existing product to a new platform.

9 A variant of the waterfall that emphasizes the verification and validation of the product.
Testing of the product is planned in parallel with a corresponding phase of development. V shaped Model Emphasize planning for verification and validation of the product in early stages of product development. Each deliverable must be testable. Project management can track progress. Easy to use. Does not easily handle dynamic changes in requirements. Does not contain risk analysis activities. Excellent choice for systems requiring high reliability – hospital patient control applications. All requirements are known. Solution and technology are known.

10 Construct a partial implementation of a total system.
Then slowly add increased functionality. The incremental model prioritizes requirements of the system and then implements them in groups. Each subsequent release of the system adds function to the previous release, until all designed functionality has been implemented. Incremental Model

11 Non Development Activities
Spiral Model Provides early indication of insurmountable risks, without much cost. Users see the system early because of rapid prototyping tools. Critical high-risk functions are developed first. Users can be closely tied to all lifecycle steps. Early and frequent feedback from users. Required Time Stopping Criteria? Non Development Activities Complex

12 Iterative Development Model
Rapid Application Development Model Use and Maintain the Accepted System Identify an End User's Information Requirements Develop Information System Prototypes Revise the Prototypes to Better Meet End User Requirements Prototyping Cycle Maintenance

13 Intelligent System Development Model
Development Round 1 (resulting in the first in house prototype) Development Round 2 Knowledge Acquisition Feasible Requirements Elicitation Testing, Implementation and Training Strategy Selection and Overall Design of KBS Ontology Selection and Knowledge Representation System Development and Implementation Knowledge Engineer ANALYSIS DESIGN DETAIL DESIGN IMPLEMENTATION Knowledge Sources and Users Requirements Middleware Services and Tools Ontology, Reusable Component Library and Standards Development Methodology for Knowledge Based System Reference taken from: Priti Srinivas Sajja and Rajendra Akerkar: “Knowledge-based systems”, Jones & Bartlett Publishers, Sudbury, MA, USA (2009)

14 Agents Agents act on behalf of users Agents are used where
Co-operation Autonomous Learning Agents are used where Expertise and resources are distributed High complexity Agents provide Modular approach Increased reusability

15 Collaborative Agent An Example of Collaborative Agent
Pilgrim Hosting System ‘Darshan’ Donation & ‘Prasad’ Ticket Reservation Site Seeing Accommodation Reservation Pilgrim Information Temple Mgt. System Legacy system managed by temple authority Bus Reser-vation System Accommodation booking, billing and administration system managed by temple authority Accommodation Booking and Administration System Ticket booking, cancelling and site seeing administration system managed by third party An Example of Collaborative Agent

16 Working of a Mobile Agent
User Optional link Application User’s Agent Other Agent An Example of Interface Agent Interface and Mobile Agents Mobile Agent Application Process Location Operating Environment Network Working of a Mobile Agent

17 Working of an Information Agent Structure of an Intelligent Agent
Network Working of an Information Agent Databases User Receives necessary information in desired format Information and Intelligent Agents Controller Executable Tasks List Goal and Objectives Interface Knowledge-Base Inference I/O Queue Structure of an Intelligent Agent

18 Multi Agent System Architecture
Repository of data and knowledge Knowledge-Base Optional Distributed Databases Midle Agent Services and Agent Meeting Place Control and Presentation Services Master Agent Interface Agent Information Agent Domain Services Domain Agent 1 Domain Agent 2 Domain Agent N Layered Architecture of Generic Multi Agent System Optional link

19 Single Agent Example - ‘Parichay’
The system gives training to adult users in multi media to speak and write Gujarati alphabets, words, sentences and numbers. The package of ‘parichay’ is accommodated in CD with auto-run facility. The touch screen facility helps even an illiterate person to identify icons and choose appropriate actions.

20 Reference taken from Sajja Priti Srinivas, “Parichay: An agent for adult literacy”, Prajna, vol.14, pp (2006) The frequent continuous development of a letter helps users to see the exact motion to write the letter. At the end of the full letter generation, the picture representing use of the letter and pronunciation is represented to the user.

21 With a notepad facility given, user may practice any letter.
That letter written by the user is matched with the correct letter by measuring shapes and angles in terms of percentages. If the degree of matching is low then user may ask to redraw/rewrite the letter.

22 Multi Agent System for Learning
Users Experts User Interface Agent Agents Learning Mgt. Drills and Quizzes Explanation Semantic Search & Chat Resource Management Question/Answer Tutorial Path Documentation Distributed Databases Local Data-Bases Resources Knowledge Mgt. Meta knowledge Conceptual system Content knowledge Learner’s ontology Mail Documents Knowledge Discovery Knowledge Utilization Knowledge Management

23 Communication between Agents
Agents developed here are communicating with a tool named KQML. Knowledge based Query Management Language. (register     : sender  agent_Learning_Mgt     : receiver agent_Tutorial-Path     : reply-with   message     : language     common_language     : ontology     common_ontology     : content      “” ) Action intended for the message Agents name sharing message Context-specific information describing the specifics of this message Ontology of both the agents Language of both agents

24 Some results form the System

25 Screen Designs of the System

26 Some of the results from System

27 Some of the results from System

28 New architecture on Grid Environment – Future extension
Users Experts User Interface Agent Agents Learning Mgt. Drills and Quizzes Explanation Semantic Search & Chat Resource Management Question/Answer Tutorial Path Documentation Internet Grid Middleware Services Resource Management (Grid Resource Allocation Protocol-GRAM) and Grid FTP Replica-Location Services Information Discovery Services Security Services Distributed databases Middleware Services and Protocols Local Data-Bases Resources Knowledge Mgt. Meta knowledge Conceptual system Content knowledge Learner’s ontology Mail Documents Knowledge Discovery Knowledge Utilization Knowledge Management

29 Towards reusable component library logic
Learning Object Repository (LOR)

30 Multi-tier KBS Accessing LOR through Fuzzy XML
Reference taken from: Sajja Priti Srinivas, “Multi-tier knowledge-based system accessing learning object repository using fuzzy XML”, in Harrison Yang & Steve Yuen (Eds.), Handbook of Research on Practices and Outcomes in E-Learning: Issues and Trends, Chapter 28, IGI Global Book Publishing, Hershey, PA, USA (2009)

31 Thanks

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