Ontology and Agent based Approach for Knowledge Management

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Ontology and Agent based Approach for Knowledge Management Powered By Docstoc
					Semantic Knowledge Model and
Architecture for Agents in
Discrete Environments

         Michal Laclavík
         Ústav informatiky
         Slovenskej akadémie vied
Outline
   Motivation
   State of the Art
   Objectives
   Methodology and Tools
   Agent Knowledge Model – Models,
    Methodology, Library
   Applications
   Conclusion
                                      2
     Motivation and State of the Art
   MAS is powerful paradigm for distributed or heterogeneous systems
   MAS need Knowledge Support and Semantics
   MAS need Connection with Existing Commercial Standards

   Agent Technology Roadmap: Current MAS Systems – lack of
    Internal Agent Knowledge Model, lack of interconnection with
    semantic web results (knowledge model representations) and
    commercial standards

   Focus on Agents and Knowledge representation (Ontologies)
   Knowledge Management and Experience Management as application
    domains



                                                                        3
    State of the Art - Agents
   Agent Definition: An agent is a computer
    system capable of flexible autonomous action in
    a dynamic, unpredictable and open environment.
    (LUCK 2003)
   MAS Standards: FIPA, MASIF
       Related to agent communication, agent platforms
       No standards for internal agent knowledge model with
        available implementations


                                                           4
State of the Art - Agents
   Architectures:
        Reactive Architecture
             No specification of knowledge model, behavior of agent is based on
              implemented responses to environment states
        Belief Desire Intention Architecture – BDI
             Belief – represents knowledge model, available some implementations
              based on logic programming, not used in FIPA compliant MAS
        Behavioral Architecture
             FIPA compliant MAS are based on such architecture
             No specification of Internal Agent Knowledge model – depend on agent
              designer and developer
   JADE Agent System
        Support for ontologies based on FIPA-SL (Similar to First Order
         Logic)
        No Query engine
        No Storage
        No Inference
                                                                                    5
    State of the Art – Ontologies, Knowledge

   Ontologies
        Knowledge Representation                          Reasoning
        OWL-DL compatible with Description                                Actions
         Logic                                          Pragmatics        Knowledge
        Query and Storage Engines available
              RDF, OWL, RDQL based                   Semantics          Information
                                                       Syntax               Data
   Application domain                                                   Characters
        Knowledge Management (KM) is the
         process through which organizations
         generate value from their intellectual and                    (Bergman, 2002,
         knowledge-based assets                                        Experience Management)
         (Source: CIO Magazine)
        Experience Management is special
         kind of KM – based on “lessons learned”




                                                                                           6
           Problem Specification
                                        Graphical User Interface


        Multi Agent System                 User requests
                                       Displaying results
                                                              XML, XML-RPC, SOAP     External
ACL          KM
                                                                                      System
          Agent 1          FIPA ACL,
IIOP,                 KIF, FIPA-SL, FIPA-RDF                Knowledge
HTTP,                                             Agent 3     Model
SMTP
                            KM

                        Agent 2           FIPA ACL,
                                        RDF/OWL, RDQL           Knowledge Storage
        Directory                                                       Querying    Knowledge
        Facilitator                                                                    Base



                                                                                                7
State of The Art Conclusion
   Focus on software, intelligent and FIPA
    compliant agents
   Providing better semantic infrastructure
    (ontologies, knowledge models)
   Apply basic principles of software and
    knowledge engineering
   Make stronger connection between MAS
    and existing commercial technologies

                                               8
    Used Tools and Software
   Protégé Ontology Editor
       Support for OWL ontology format
       Can be used as modeling tool
   JADE (Java Agent DEvelopment
    Framework)
       Most developing MAS framework
       Compliant with FIPA standards
   Jena – Semantic Web Framework for Java
       Support for OWL – best available OWL API
       Support for RDQL model querying

                                                   9
Agent Knowledge Model

 Objective:
 Design of Agent Architecture using
 Ontology based Knowledge Model
        Agent Knowledge Model
   Based on Events, Resources, Actions, Actors, Context
   Formally Described using Sets, Description Logic
    (compatible with OWL-DL), Graph Representation
   Actor Context updating function/algorithm
    (Actor Environment State)
       CAnew = fC(ea,CAold)
   Resources updating function/algorithm
    (result of fulfilled actor goals)
       RAnew = fR(CAnew,RAold)




                                                           11
Software Development
Methodology

 Objective:
 Design of Software Development
 Methodology for creation of Agents
 with Ontology based Knowledge Model
Development Methodology
(Knowledge Model)
   Extending Model with Protégé Editor following
    CommonKADS models
       Organizational or Environment Model
       Task Model
       Agent or Actor Model
            Includes implementation of algorithms for context and resource
             updating
   Results
       Ontology developed in Protégé which can be exported in
        OWL format.
       Concrete Algorithms for each actor (often algorithms are
        similar or same) which updates actors' context CAnew and
        resources RAnew.


                                                                         13
     Development Methodology
     (System Design)
   UML Diagrams for concrete Application Domain
   Use Case Diagram
       for each agent
       agent is taken as system
        boundaries
   Sequence Diagram
       Communication among
        agents
   Class Diagram
       Behaviors are described as methods



                                                   14
Agent Software Library
 Objectives:

 Design of Agent Architecture using
 Ontology based Knowledge Model

 Design & Development of Software Library for building
 Intelligent Agents with Ontology Knowledge Model with
 possibility to plug agents to existing commercial technologies
    Agent Software Library
   Support for OWL based Agent Knowledge Model
   Support for XML-RPC connection to receive event and
    send plain XML
   Support for agent communication using FIPA ACL with
    OWL and RDQL as content languages
   Support for Presentation of Ontological Knowledge
    (RDF/OWL => plain XML + XSL => HTML)
   JADE and Jena Integration
   Available on JADE official website
    to MAS community




                                                          16
Agent Library Example




                        17
Support for Knowledge and
Experience Management

 Objective:
 Design of Generic Ontology Model for
 Experience Management with extension to
 different application domains.
     Extension of Model for
     Experience Management
   Extended Agent Memory
    Model

   Workflow Related
        WfInstance, WfActivity
   ActiveHint
        Sub class of resource
        Representation of
         Experience
   Employee




                                  19
Presentation of Ontology
based Knowledge

 Objective:
 Design and Development of user
 friendly Knowledge Presentation for
 MAS.
        Presentation of Ontology
        based Knowledge
   Ontology Tree
       Browse window
   Graph
   XSL Transformation
       RDF/OWL => Plain XML +
        XSL => HTML
       Infrastructure to receive
        plain XML using XML-RPC




                                    21
Applications

 Objective:
 Evaluation of Results on real
 pilot operation.
Pellucid 5FP IST Project
                                           Pellucid Architecture
   Title: Platform for Organizationally
    Mobile Public Employees
   Duration: Sep 2002- Dec 2004
   Knowledge Management to support
    employees
   Workflow based Administration
    Processes
   To support Employee Mobility in                        Pellucid Agents
    organization
    Agent Architecture based on
                                                           Interaction Layer

    autonomous co-operating agents         Process Layer




                                                                               23
     Pellucid Applications

   CDG, Genoa, Italy
    Traffic Light Management
   MMBG, Sanlucar, Spain
    Project Management
   SADESI, Seville, Spain
    Telephone Incidence
    Resolution


                               24
        K-Wf Grid 6FP IST Project
   Title: Knowledge-based Workflow System for Grid
    Applications
   Objectives: To support workflow construction and
    execution with Knowledge
   Duration: Sep 2004 - Feb 2007



                          Work on new EMBET architecture
                          Current state: User Assistant Agent in K-Wf Grid uses model
                           presented in thesis.
                          Algorithms presented in chapter 5 were reused with same
                           improvements and modifications.
                          Architecture is not Agent based but users of system are
                           modeled as actors.
                          Knowledge Model, its implementation and modified
                           algorithms presented
                           in thesis are used

                                                                                         25
Conclusion and Future Work
        Conclusion (1)

   The most significant scientific achievements
       Agent knowledge model
            Applicable in any discrete environment where actors need to be
             modeled
            Can be expressed by ontology, sets or description logic
       Such model was found useful for:
            Simple goal oriented agents
            Knowledge Management Solution based on Agents (Pellucid)
            Experience Management Solution non agent based (EMBET
             System)
       Development Methodology
            Speed up Knowledge based Agent development for concrete
             application domains
                                                                              27
        Conclusion (2)
   The most significant development achievements
       Agent Library
            Support for OWL based Agent Knowledge Model
            Support for XML-RPC connection to receive event and send plain XML
            Support for Presentation of Ontological Knowledge (RDF/OWL => plain
             XML + XSL => HTML)
            Support for agent communication using FIPA ACL with OWL and RDQL
             as content languages
            JADE and Jena Integration
            Available on JADE official website to MAS community
             (year 2005 – 577 downloads)




                                                                                   28
Thank you !

 Michal Laclavik

				
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