Ontology and Agent based Approach for Knowledge Management
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Ontology and Agent based
Approach for Knowledge
Management
Defense of PhD Thesis
Michal Laclavík
Supervisor: Ing. Ladislav Hluchý PhD.
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 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”
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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
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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
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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)
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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.
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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
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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
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Agent Library Example
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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
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Algorithms for
EM Extension
Actor (Employee)
Context updating
algorithm
CAnew = fC(ea,CAold)
Resources (Active Hint)
updating algorithm
RAnew = fR(CAnew,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 sim({res1,res2}) = fsim(
"{propi} propertyi.Resource({res1})
Individuals "{propj} propertyj.Resource({res2})
{propi} {propj} {propi} DomainClass
Weighted matching of DomainClass Domain
${simWeight} SimilarityWeight
properties domainClass.SimilarityWeight( DomainClass) {simWeight}
{weight} weight .SimilarityWeight( DomainClass) {simWeight};
Sij{weight}/n
Similar to CBR )
algorithm Weighted
Euclidian Distance
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Presentation of Ontology
based Knowledge
Objective:
Design and Development of user
friendly Knowledge Presentation.
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
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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
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Pellucid Applications
CDG, Genoa, Italy
Traffic Light Management
MMBG, Sanlucar, Spain
Project Management
SADESI, Seville, Spain
Telephone Incidence
Resolution
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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
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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
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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
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Thank you !
Thank You for you attention
Many Thanks to my supervisor
Many Thanks to my colleagues
Many Thanks to the Reviewers for their helpful and
constructive comments and for reading my thesis
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