Ontology and Agent based Approach for Knowledge Management
Defense of PhD ThesisMichal LaclavíkSupervisor: Ing. Ladislav Hluchý PhD.
Bratislava, 12th January 2006 2
Outline Motivation State of the Art Objectives Methodology and Tools Agent Knowledge Model – Models,
Methodology, Library Experience Management Applications Conclusion
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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
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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
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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
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State of the Art – Ontologies,
Knowledge
Ontologies Knowledge Representation OWL-DL compatible with Description
Logic Query and Storage Engines
available RDF, OWL, RDQL based
Application domain Knowledge Management (KM) is
the process through which organizations generate value from their intellectual and knowledge-based assets (Source: CIO Magazine)
Experience Management is special kind of KM – based on “lessons learned”
Characters
Data
Information
Knowledge
Actions
Syntax
Semantics
Pragmatics
Reasoning
(Bergman, 2002, Experience Management)
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Problem Specification
Multi Agent System
Agent 1
Agent 2
Agent 3
Graphical User Interface
External System
Knowledge Base
DirectoryFacilitator
Knowledge StorageQuerying
XML, XML-RPC, SOAP
User requestsDisplaying results
FIPA ACL, KIF, FIPA-SL, FIPA-RDF
FIPA ACL,RDF/OWL, RDQL
Knowledge Model
KM
KM
IIOP, HTTP, SMTP
ACL
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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
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Thesis Objectives Design of Agent Architecture using
Ontology based Knowledge Model Design of Software Development Methodology for
creation of Agents with Ontology based Knowledge Model
Design of Generic Ontology Model for Experience Management with extension to different application domains.
Design & Development of Software Library for building Intelligent Agents with Ontology Knowledge Model with possibility to plug agents to existing commercial technologies
Design and Development of user friendly Knowledge Presentation.
Evaluation of Results on real pilot operation.
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Used Methods and Methodologies
Knowledge management, system design Unified Modeling Language – UML CommonKADS, MAScommonKADS Protégé as Tool for CommonKADS
Formal methods for describing ontology based models Description Logic Graph Ontology representation
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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
Agent Knowledge Model
Objective:Design of Agent Architecture using Ontology based Knowledge Model
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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,CA
old) Resources updating function/algorithm
(result of fulfilled actor goals) RA
new = fR(CAnew,RA
old)
Software Development Methodology
Objective:Design of Software Development Methodology for creation of Agents with Ontology based Knowledge Model
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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 CA
new and resources RAnew.
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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
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
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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
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Agent Library Example
Support for Knowledge and Experience Management
Objective:Design of Generic Ontology Model for Experience Management with extension to different application domains.
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Extension of Model for Experience Management
Extended Agent Memory Model
Workflow Related WfInstance, WfActivity
ActiveHint Sub class of resource Representation of
Experience Employee
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Algorithms for EM Extension
Actor (Employee) Context updating algorithm
CAnew = fC(ea,CA
old)
Resources (Active Hint) updating algorithm
RAnew = fR(CA
new,RAold)
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Complexity of algorithms All depends also on Active Hints
Templates count – this does not grow too fast.
1st Case: Constant – final count of context elements (1-6)
2nd Case: O(n) – based on resource/event count in Memory
3rd Case: O(n2) – based on 2 loops: events/resources, similar resources
experimental solution because algorithm used other software e.g. Jena with RDQL – it was hard to prove complexity different way.
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Resource Similarity (3rd Case)
Similarity of Ontology Individuals
Weighted matching of properties
Similar to CBR algorithm Weighted Euclidian Distance
sim({res1,res2}) = fsim( {propi} propertyi.Resource({res1})
{propj} propertyj.Resource({res2}) {propi} {propj} {propi} DomainClass
DomainClass Domain {simWeight} SimilarityWeight domainClass.SimilarityWeight( DomainClass) {simWeight}
{weight} weight .SimilarityWeight( DomainClass) {simWeight};ij{weight}/n
)
Presentation of Ontology based Knowledge
Objective:Design and Development of user friendly Knowledge Presentation.
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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
Applications
Objective:Evaluation of Results on real pilot operation.
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Pellucid 5FP IST Project 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 organization Agent Architecture based on
autonomous co-operating agents
Process Layer
Interaction Layer
Pellucid Architecture
Pellucid Agents
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Pellucid Applications
CDG, Genoa, ItalyTraffic Light Management
MMBG, Sanlucar, SpainProject Management
SADESI, Seville, SpainTelephone Incidence Resolution
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K-Wf Grid 6FP IST Project
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
Title: Knowledge-based Workflow System for Grid Applications
Objectives: To support workflow construction and execution with Knowledge
Duration: Sep 2004 - Feb 2007
Conclusion and Future Work
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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
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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
(August - December 2005 – 314 downloads)
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Conclusion (3)
Extension of Work for Experience Management Model Algorithms
Projects Motivation for solving problems in
real Application Evaluation of Thesis results
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Future work RAPORT APVT project (01/2005-12/2007): Research and
development of a knowledge based system to support workflow management in organizations with administrative processes
model and algorithms will be reused and extended
K-Wf Grid EU 6FP RTD IST project (2004-2007) evaluation on more applications, improvement of context
detection
NAZOU SPVV Project (09/2004-11/2007): Tools for acquisition, organization and maintenance of knowledge in an environment of heterogeneous information resources
OnTeA semantic annotation – not directly related but can be used for context detection
Thank you !
Thank You for you attentionMany Thanks to my supervisorMany Thanks to my colleaguesMany Thanks to the Reviewers for their helpful and constructive comments and for reading my thesis