TIES-423%20(TLI363)%20

1
TIES-423 (TLI363) Agent Technologies in Mobile
Environment former nameTLI371 Distributed
Artificial Intelligence in Mobile
EnvironmentCourse Introduction
Spring-2007

• Vagan Terziyan
• Department of Mathematical Information Technology
• University of Jyvaskyla
• vagan_at_it.jyu.fi terziyan_at_yahoo.com
• http//www.cs.jyu.fi/ai/vagan
• 358 14 260-4618

2
Contents

• Course Introduction
• Lectures and Links
• Course Assignment
• Course Exercise

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Practical Information

• 12 Lectures (2 x 45 minutes each, in English)
  during period 12 March - 24 April according to
  schedule
• 8 lectures by Vagan Terziyan theory
• 4 lectures by Artem Katasonov theory and
  practice
• 4 Laboratory works in computer class (2 x 45
  minutes each, in English) during period 7 May -
  15 May according to schedule, by Artem Katasonov
• Slides for lectures available online
• Assignment. Based on the theoretical part of the
  course. Make PowerPoint presentation based on a
  research paper)
• Group Exercise. Based on the practical part of
  the course and related to design of a multi-agent
  system with SmartResource Platform (a tool on the
  top of JADE)
• Exercise and assignment should be available for
  review until 31 May (2400)
• Exam There will be no exam. Course grade will be
  given based on the exercise and assignment
  quality.

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Lectures Topics and Schedule (1)

• 12 March 2007 Course Introduction (today)
• Lecture 1 - Agent Technologies in Mobile
  Environment Course Introduction
• 13 March 2007 Overview of Intelligent Agents
• Lecture 2 - What is an Intelligent Agent ?
• 19 March 2007 Overview of (Multi)Agent
  Technologies - I
• Lecture 3 - Agent Technologies - I
• 20 March 2007 Overview of (Multi)Agent
  Technologies - II
• Lecture 4 - Agent Technologies - II
• 26 March 2007 Agent Intelligence I
• Lecture 5 - Agent Logic, Reasoning and
  Planning
• 27 March 2007 Agent Intelligence II
• Lecture 6 - Agent Learning and Knowledge
  Discovery
• 2 April 2007 Industrial Applications of Agent
  Technology - I
• Lecture 7 - SmartResource Agent-Based
  Self-Managed Web Resources - I
• 3 April 2007 Industrial Applications of Agent
  Technology - II

Ag. C134.1
Ag. Auditorio 2
Ag. C233.1
Monday lectures 1215 1355 Break 1300
1310 Place Agora Alfa
Tuesday lectures 1015 1155 Break 1100
1110 Place Agora Alfa
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Lectures Topics and Schedule (2)

• 16 April 2007 Agents as a Novel Software
  Engineering Paradigm
• Lecture 9 - Agent-Oriented Software
  Engineering
• 17 April 2007 Agent Platforms
• Lecture 10 - Agent Standards and Platforms
• 23 April 2007 Introduction to JADE Programming
• Lecture 11 - Introduction to JADE
• 24 April 2007 Development with SmartResource
  Platform
• Lecture 12 - SmartResource Platform
• 7 May 2007 Agent Design Lab - I
• Lab. work 1 - Getting started with JADE
• 8 May 2007 Agent Design Lab - II
• Lab. work 2 - Development for SmartResource
  I
• 14 May 2007 Agent Design Lab - III
• Lab. work 3 - Development for SmartResource
  II
• 15 May 2007 Agent Design Lab - IV
• Lab. work 4 - Development for SmartResource
  III

Place Computer Class
Monday lectures 1215 1355 Break 1300
1310 Place Agora Alfa
Tuesday lectures 1015 1155 Break 1100
1110 Place Agora Alfa
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Course Motivation

• Growing complexity of computer systems and
  networks used in industry ? need for new
  approaches to manage and control them
• IBM vision Autonomic computing Self-Management
  (includes self-configuration, self-optimization,
  self-protection, self-healing)
• Ubiquitous computing, Internet of Things ? huge
  numbers of heterogeneous devices are
  interconnected
• nightmare of pervasive computing when almost
  impossible to centrally manage the complexity of
  interactions, neither even to anticipate and
  design it.
• We believe that self-manageability of a complex
  system requires its components to be autonomous
  themselves, i.e. be realised as agents.
• Agent-based approach to SE is also considered to
  be facilitating the design of complex systems

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INTEL Proactive Computing Concept (1)

• Intel Research initiated work on Proactive
  Computing (beginning 2001) - working towards
  environments in which networked computers
  proactively anticipate our needs and, sometimes,
  take action on our behalf.
• Intel identified three steps that are essential
  to making proactive computing a reality
• The first is getting physical connecting
  billions of computing devices directly to the
  physical world around them so that human beings
  are no longer their principal I/O devices.
• The next step is getting real having computers
  running in real time or even ahead of real time,
  anticipating human needs rather than simply
  responding to them
• The third step is getting out extending the
  role of computers from the office and home into
  the world around us and into new application
  domains.

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INTEL Proactive Computing Concept (2)
Intel Research is exploring computing futures
that overlap autonomic computing but also explore
new application domains that require principles
we call proactive computing, enabling the
transition from todays interactive systems to
proactive environments that anticipate our needs
and act on our behalf. (R. Want, T.
Pering, D. Tennenhouse, Comparing Autonomic
and Proactive Computing, IBM Systems Journal,
Vol 42, No 1, 2003)

• Proactive system design is guided by seven
  underlying principles
• connecting with the physical world,
• deep networking,
• macro-processing,
• dealing with uncertainty,
• anticipation,
• closing the control loop,
• making systems personal.

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IBM Autonomic Computing (1)

• The computing domain is now a vast and diverse
  matrix of complex software, hardware and
  services. By 2020 we expect billions of devices
  and trillions of software processes, with a lot
  of data. And it's not just a matter of numbers.
  It's the complexity of these systems and the way
  they work together that is creating a shortage of
  skilled IT workers to manage all of the systems.
  It's a problem that's not going away, but will
  grow exponentially, just as our dependence on
  technology has.
• Autonomic Computing is about how to enable
  computing systems to operate in a fully
  autonomous manner. No administration, just simple
  high-level policy statements.
• Autonomic Computing is an approach to
  self-managed computing systems with a minimum of
  human interference. The term derives from the
  body's autonomic nervous system, which controls
  key functions without conscious awareness or
  involvement.

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IBM Autonomic Computing (2)
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IBM Service-Oriented Architecture (1)

• Message from the Vice President, IBM Asset
  and Integration Technology, Software Group
• As we regard the advances that have moved us
  into the 21st century, we observe that
  information technology (IT) seems to repurpose
  itself almost every year. Like the invention of
  transistors the new service-oriented thinking
  and its application to IT known as
  service-oriented architecture (SOA) distinguishes
  itself as a paradigm change. Seen in the context
  of an entirely new service-oriented business
  ecosystem, SOA could be one of the most
  significant technological advances, enabling the
  IBM corporate strategy of business on demand...
• Business processes must be decomposed, services
  must be created, and the supporting machinery
  must be implemented, so that the business
  ecosystem can run effectively, efficiently, and
  manageably.
• IBM has found that businesses which made the
  transition to service-oriented enterprises have
  shown significant savings in maintenance,
  personnel, and software and hardware costs. This
  transition starts with the use of the Component
  Business Model (CBM) and continues with the
  application of Service Oriented Modeling and
  Architecture (SOMA)...

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IBM Service-Oriented Architecture (2)

• In the current business environment in which
  companies are under increasing pressure not only
  to increase revenue but also to respond quickly
  to changing market conditions, companies will be
  successful only if they transform themselves and
  become on demand businesses.
• Needed transformation changes include
  componentization and service-orientation.
• Componentization enables a business to operate in
  a value net, a network of partnerships with
  customers and suppliers supported by real-time
  information flows and information technology
  systems.
• Service-orientation is needed to achieve seamless
  integration of business components.
• Recent IBM activities and experiences in this
  area prove high business value for these
  challenges.

L. Cherbakov, G. Galambos, R. Harishankar, S.
Kalyana, and G. Rackham, Impact of service
orientation at the business level, In
Service-Oriented Architecture, IBM Systems
Journal ,   Volume 44, Number 4, December 2005.
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The Theatre metaphor
TAPAS
Theatre A metaphor for concepts and
functionality definition.
Repertoire The set of Plays that may be
performed at the theatre.
Play Defines a set of logically related
functionality.
Director role figure The manager of plays, and
supervisor for application role figures,
constituted by an actor .
Application role figures The performers of
plays. Constituted by actors playing roles.
Capability A unique set of properties of an
actor at the stage where he is playing.
Role session A dialogue between two role figures.
Actors
Manuscript The assigned behavior, i.e. the
defined role of a role figure, constituted by an
an actor.
Norwegian University of Science and Technology,
Trondheim
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Google Excellent content and context provider
for Web applications

• Google Maps,
• Google Earth,
• Wikimapia,
• GMail,
• Blogger,
• etc.

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Two alternative trends of Web development
Machines, devices, software, etc
Human Communities
Semantic Web
Web 2.0
Facilitates Human-to-Human interaction
Metadata
Wikis
Ontologies
Blogs
Facilitates Machine-to-Machine interaction
SW Services
Mashups
Agents
Web-Services
EAI Portals
Web
Community Portals
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What is Wiki

• Wiki is the simplest online database that could
  possibly work.
• Wiki is a piece of server software that allows
  users to freely create and edit Web page content
  using any Web browser.
• Wiki supports hyperlinks and has a simple text
  syntax for creating new pages and crosslinks
  between internal pages on the fly.
• Wiki is unique among other group communication
  mechanisms because it allows editing the
  organization of content in addition to the
  content itself.
• Wiki encourages democratic use of the Web by
  promoting content composition by non-technical
  users.

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Sample of Wiki Web page
Collaborative editing window
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Wikipedia
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Web 2.0 Community Portal
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Motivation for Semantic Web
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Semantic Web New Users
applications
agents
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Semantic Web Resource Integration
Semantic annotation
Shared ontology
Web resources / services / DBs / etc.
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Semantic Web which resources to annotate ?
This is just a small part of Semantic Web concern
!!!
Technological and business processes
External world resources
Web resources / services / DBs / etc.
Semantic annotation
Shared ontology
Multimedia resources
Web users (profiles, preferences)
Web agents / applications / software components
Smart machines, devices, homes, etc.
Web access devices and communication networks
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GUN Concept
GUN Global Understanding eNvironment
GUN Global Environment Global Understanding
Proactive Self-Managed Semantic Web of
Things (we believe) Killer Application for
Semantic Web Technology
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GUN and Ubiquitous Society
GUN can be considered as a kind of Ubiquitous
Eco-System for Ubiquitous Society the world in
which people and other intelligent entities
(ubiquitous devices, agents, etc) live together
and have equal opportunities (specified by
policies) in mutual understanding, mutual service
provisioning and mutual usability.
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Core technologies for GUN
Distributed Artificial Intelligence
Semantic Technology

• Interoperability, Automation and Integration
• Reusable semantic history blogs
• Reusable semantic behavior patterns and process
  descriptions
• Reusable coordination, design, integration and
  composition patterns
• Reusable decision-making patterns
• Reusable interface patterns
• Reusable security and privacy policies

• Proactivity
• Autonomic behavior
• Communication, coordination, negotiation,
  contracting
• Self-Configuration and Self-Management
• Learning based-on liveblog histories
• Data Mining and knowledge discovery
• Dynamic integration
• Diagnostics and prediction
• Model exchange and sharing

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GUN-GERI-UBIWARE-SmartResource ?
http//www.cs.jyu.fi/ai/OntoGroup/projects.htm
GUN (Global Understanding Environment)
Proactive Self-Managed Semantic Web of Things -
general concept and final destination GERI
(Global Enterprise Resource Integration) GUN
subset related to industrial domains UBIWARE
middleware for GERI SmartResource semantic
technology, pilot tools and standards for UBIWARE
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SmartResource in the IOG Web Site
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One of Smart Resource Scenarios
Knowledge Transfer from Expert to Service
Agent plays roles Scene 1 diagnostic
expert Scene 2 no play Scene 3 no play
Expert
Labelled data
Agent plays roles Scene 1 no play Scene 2
student Scene 3 diagnostic expert
Watching and querying diagnostic data
Querying diagnostic results
Device
Service
Labelled data
History data
Querying data for learning
Learning sample and Querying diagnostic results
Agent plays roles Scene 1 patient Scene 2
teacher Scene 3 patient
Diagnostic model
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Agent-driven EAI (1)
manager
expert
operator
owner
field crew
consumers
administration
USERS
UBIWARE
Production
Services
External Applications
Maintenance
Intelligence
Enterprise portal
Automation
Data Warehouse
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Agent-driven EAI (2)
AI tools (Knowledge Discovery)
Software and services
Maintenance workers
Sensors and alarm detectors
Experts
Operators
UBIWARE
Resource info
Other users
UBIWARE
Data Warehouse
Industrial Resource
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Agents in mobile environment
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Agent-driven EAI in mobile environment
manager
administration
customers
Expert/specialist
Call center
field crew
UBIWARE
Data Warehouse
Intelligence
GPS
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Agent-driven integration in mobile environment
3G WWAN
Operating on 3G WWAN
Zone 1
Zone 2
Zone 3
Plug into power jack Wakeup Wi-Fi Continue over
Wi-Fi
Wakeup Wi-Fi
Zone 6
Zone 5
Zone 4
Airport
Wi-Fi Link Going Down.
Connect to Wi-Fi
Home
Continue session on 3G WWAN
Continue session on Wi-Fi
Battery level low Shutdown WiMAX Switch to 3G WWAN
Operator initiated switch to WiMAX Continue
session on WiMAX Shutdown Wi-Fi
WiMAX
WiMAX
Zone 7
Zone 9
Zone 8
IEEE 802.21 for Network Discovery
IEEE 802.21, SIP, VCC, IMS, for Network Selection
and Service Continuity across multiple radios
(3G WWAN ?? Wi-Fi ?? WiMAX)
802.21, SIP, IMS for Service Continuity (Wi-Fi
?? WiMAX)
VCC, SIP, IMS for Call Continuity (3G WWAN
?? Wi-Fi)
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Agent-driven peer-to-peer environments

• JADE-LEAP Agent Platform is extension to JADE
  (special container within JADE)
• Target devices
• Java MIDP-capable phones
• PDA devices
• Smallest available platform in terms of footprint
  size
• Proprietary device-initiated and socket based
  communication channel with main container
• Developed within LEAP project
• Open-source

Mikko Laukkanen
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Agent-Driven EAI (Human-Centric)
2
Human as UBIWARE service provider
Online Monitoring
Sensing
Treatment
Testing
Diagnostics
UBIWARE
Human as UBIWARE administrator
Human as UBIWARE user (utilizing integrated data
and knowledge)
Human as UBIWARE Resource (i.e. service consumer)
4
Data Warehouse
UBIWARE
1
3
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Word-Wide Correlated Activities
Semantic Web
Agentcities is a global, collaborative effort to
construct an open network of on-line systems
hosting diverse agent based services.
Semantic Web is an extension of the current web
in which information is given well-defined meaning
, better enabling computers and people to work
in cooperation
Agentcities
Grid Computing
Wide-area distributed computing, or "grid
technologies, provide the foundation to a number
of large-scale efforts utilizing the global
Internet to build distributed computing and
communications infrastructures.
FIPA
FIPA is a non-profit organisation aimed at
producing standards for the interoperation of
heterogeneous software agents.
Web Services
WWW is more and more used for application to
application communication. The programmatic
interfaces made available are referred to as Web
services. The goal of the Web Services Activity
is to develop a set of technologies in order to
bring Web services to their full potential
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Package of courses
Java programming, AI basics
Spring
Fall
Design of distributed, self-descriptive,
autonomous, proactive, self-managed,
interoperable, intelligent systems, applications
and services
39
ATME Course Lectures
40
Lecture 1 This Lecture - ATME Introduction
http//www.cs.jyu.fi/ai/vagan/ATME_Introduction.pp
t
41
Lecture 2 What is an Intelligent Agent ?
http//www.cs.jyu.fi/ai/vagan/Agents.ppt
42
Lectures 3-4 Agent Technologies (Mobility,
Communication, Coordination, Negotiation)
http//www.cs.jyu.fi/ai/vagan/Agent_Technologies.p
pt
43
Lectures 5-6 Agent Intelligence (Internal Logic,
Reasoning, Planning, Learning, Knowledge
Discovery)
http//www.cs.jyu.fi/ai/vagan/Agent_Intelligence.p
pt
44
Lectures 7-8 Industrial Applications of Agent
Technology SmartResource - Agent-Based
Self-Managed Web Resources
http//www.cs.jyu.fi/ai/vagan/SmartResource_Summar
y.ppt
45
Lecture 9 Agents as a Novel Software Engineering
Paradigm

• Agents as a novel Software Engineering paradigm
• Benefits
• Agent platforms and agent programming languages
  (APL)
• Potential effect on problem analysis and
  requirements processes

This and following lectures are by Artem Katasonov
http//people.cc.jyu.fi/akataso/ties423/Lecture9.
pdf
46
Lecture 10 Agent Platforms

• FIPA (IEEE) architecture
• Existing platforms
• JADE
• Cougaar
• AgentFactory
• 3APL
• Jason (AgentSpeak APL)
• SmartResource Platform

http//people.cc.jyu.fi/akataso/ties423/Lecture10
.pdf
47
Lecture 11 Introduction to JADE

• Architecture
• System agents and their GUIs
• Main classes (Agent, Behaviour) and their
  abilities

http//people.cc.jyu.fi/akataso/ties423/Lecture11
.pdf
see also
http//www.cs.jyu.fi/ai/vagan/JADE_Agents.ppt
48
Lecture 12 SmartResource Platform

• Architecture
• Script language (semantic APL)
• Developing Reusable Atomic Behaviors (RABs)

http//people.cc.jyu.fi/akataso/ties423/Lecture12
.pdf
49
ATME Course Assignment
50
Assignment in brief

• Students are expected to select one of below
  recommended papers (or any other relevant
  research paper from the Web) and make PowerPoint
  presentation based on that paper. The
  presentation should provide evidence that a
  student has got the main ideas of the paper, is
  able to provide his personal additional
  conclusions and critics to the approaches used.

51
Evaluation criteria for the assignment

• Content and Completeness
• Clearness and Simplicity
• Discovered Connections to ATME Course Material
• Originality, Personal Conclusions and Critics
• Design Quality.

52
Format, Submission and Deadlines

• Format PowerPoint .ppt , name of file is
  students family name
• Presentation should contain all references to the
  materials used, including the original paper
• Deadline - 31 May 2007 (2400)
• Files with presentations should be sent by e-mail
  to Vagan Terziyan (vagan_at_it.jyu.fi and
  artem.katasonov_at_jyu.fi)
• Notification of evaluation - until 10 June.

53
Papers for Course Assignment (1)

• Paper 1 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_1_P.pdf
• Paper 2 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_2_P.pdf
• Paper 3 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_3_CF.pdf
• Paper 4 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_4_CF.pdf
• Paper 5 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_5_MW.pdf
• Paper 6 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_6_BN.pdf
• Paper 7 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_7_BN.pdf
• Paper 8 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_8_MM.pdf

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Papers for Course Assignment (2)

• Paper 9 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_9_WM.pdf
• Paper 10 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_10_WM.pdf
• Paper 11 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_11_III.pdf
• Paper 12 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_12_III.pdf
• Paper 13 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_13_KM.pdf
• Paper 14 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_14_ES.pdf
• Paper 15 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_15_MDB.pdf
• Paper 16 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_16_MDB.pdf

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ATME Course Group Exercise
56
Group Exercise in brief

• In small groups of 2-4 people
• Based on the practical part of the course and
  related to design of a multi-agent system with
  SmartResource Platform.
• At least some members of the group should have
  some experience in JAVA programming (for
  developing RABs).
• Since a major part of development work under
  SmartResource Platform is done through high-level
  scripting in semantic APL, students without
  experience in JAVA can participate as well,
  taking these tasks.
• Deadline - 31 May 2007 (2400)
• Source files and minimal documentation should be
  sent by e-mail to Artem Katasonov
  (artem.katasonov_at_jyu.fi).

57
Information about Related Course

• Agent Technologies in the Semantic Web
• http//www.cs.jyu.fi/ai/vadim/
• by Vadim Ermolayev
• recommended as additional reading.

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Additional reading (1) Agent Reasoning with
Uncertainty Introduction to Bayesian Networks
http//www.cs.jyu.fi/ai/vagan/Bayes_Nets.ppt
59
Additional Reading (2) Personalization in Mobile
Environment
http//www.cs.jyu.fi/ai/vagan/Mobile_Personalizati
on.ppt
60
Additional slides (old content)
61
Distributed AI Applications
Application Area
Web Content Management
Emerging Application
Personalization
Distributed transactions management
Agent technologies
Solutions
Profile / Location management
Data mining
Knowledge metamodeling
Beliefs management
Filtering
62
Some Professions around Semantic Web
AI Professionals
Content creators
Content
Logic, Proof and Trust
Mobile Computing Professionals
Web designers
Ontologies
Agents
Annotations
Ontology engineers
Software engineers
63
Lecture n Agents for Personalizing Web
Resources Web Content Personalization Overview
http//www.cs.jyu.fi/ai/vagan/Personalization.ppt
64
Lecture nn Collaborative Filtering
http//www.cs.jyu.fi/ai/vagan/Collaborative_Filter
ing.ppt
65
Lecture nnn Similarity Evaluation Techniques for
Filtering
http//www.cs.jyu.fi/ai/vagan/Similarity_in_Filter
ing.ppt
66
Lecture nn Agent-based Knowledge Discovery
Dynamic Integration of Virtual Predictors
http//www.cs.jyu.fi/ai/vagan/Virtual_Predictors.p
pt
67
JADE (Java Agent DEvelopment Platform)
68
Agent Standards FIPA Agent Framework
http//www.cs.jyu.fi/ai/vagan/Agent_Standards.ppt
69
ATME Course Exercise
70
Task for the Exercise (according to A. Raja) (1)

• Consider the home of the future where there
  are software agents in a mobile environment that
  are helping to manage the running of a house.
  There will be
• (1) Personal assistant agents that will know of
  your preferences of temperature, humidity, light,
  sound, etc., and who you want to interact with
• (2) There will be agents that can measure
  appropriate environmental conditions with
  specific devices
• (3) There will be agents that effect appropriate
  environmental conditions with specific devices
• (4) There will be agents that control expenses
  for the use of appropriate devices
• (5) There will be agents that manage the
  telephone communications
• (6) There will be agents that manage security
  issues such as fire, earthquake, flood
  protection, etc.

71
Task for the Exercise (according to A. Raja) (2)

• Assume that the agents are heterogenous (i.e.
  have not be generated by one designer), for
  example when you get a new device it will come
  with an agent for instance, the heating
  measurement agent may not come from the same
  company as the air-conditioning agent.
• Think about the possibility of having these
  agents work together. What are the capabilities
  of the agents, what type of cooperation needs to
  occur among them, are there needs for the agents
  to negotiate, are there situations where local
  objectives are at odds with global objectives
  such as minimizing electrical usage? What type of
  information needs to be exchanged among the
  agents?

72
Task for the Exercise (according to A. Raja) (3)

• How would you organize the agents would you
  have a hierarchy of agents in terms of their
  control responsibilities? How would you allow
  agents to integrate new agents into the system,
  for instance, when you buy a new device.
• What are the specific characteristics required by
  a language in order that these agents can share
  information? If there are no dedicated resources
  for each agent, but rather a pool of resources
  that can be used by agents, what new issues does
  this introduce? Do agents need to reason about
  the intentions of other agents?

73
Task for the Exercise (according to A. Raja) (4)

• In answering these and related issues that you
  may consider, please be concrete with specific
  and numerous examples/scenarios. You should first
  start out the effort by detailing the collection
  of agents that you see in the house of the
  future, what their responsibilities are, and
  their patterns of interaction with other agents.
  Including figures, it should be at least 5 pages
  long.

74
Format, Submission and Deadlines

• Format MS Word doc. (winzip encoding allowed),
  name of file is students family name
• Presentation should contain all references to the
  materials used
• Deadline - 20 October 2004 (2400)
• Files with presentations should be sent by e-mail
  to Vagan Terziyan (vagan_at_it.jyu.fi)
• Notification of evaluation - until 29 October.