TLI371

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TLI371 Distributed Artificial Intelligence in
Mobile EnvironmentCourse Introduction

• 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

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Contents

• Course Introduction
• Lectures and Links
• Course Assignment
• Course Exercise
• Examples of course-related research

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Practical Information

• 8 Lectures (2 x 45 minutes each, in English)
  during period 21 November - 13 December according
  to the schedule
• Slides available online plus hardcopies will be
  given
• Exercise (Write 3-5 pages description of possible
  solution of a given research problem)
• Assignment (Make PowerPoint presentation file
  based on a research paper. Oral presentation is
  not required)
• Exercise and assignment should be sent
  electronically to the lecturer until 13 December
  (2400)
• Exam 16 December, 1200. There will be no exam
  for students who will submit the course exercise
  and assignment within the deadline and at least
  of satisfactory quality. Course mark in this case
  will be given based on the exercise and
  assignment.

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Lectures Topics and Schedule

• 21 November 2002 DAI Introduction and Web
  Content Personalization (today)
• Lecture 0 - DAI in Mobile Environment Course
  Introduction
• Lecture 1 - Web Content Personalization
  Overview
• 22 November 2002 Overview of Intelligent
  Agents
• Lecture 2 - What is an Intelligent Agent ?
• 28 November 2002 Overview of (Multi)Agent
  Technologies I
• Lecture 3 - Agent Technologies (1)
• 29 November 2002 Overview of (Multi)Agent
  Technologies II
• Lecture 4 - Agent Technologies (2)
• 5 December 2002 Overview of Filtering
  Techniques for Personalization
• Lecture 5 - Collaborative Filtering
• 6 December 2002 Probabilistic Networks for
  Personalization
• Lecture 6 - Introduction to Bayesian
  Networks

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DAI in Mobile Environment (example)
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Distributed Artificial IntelligenceA. Tveit,
DAI Course

• DAI is a sub-field of AI
• DAI is concerned with problem solving where
  agents solve (sub-) tasks
• Main areas of DAI
• Multi-Agent Systems
• Distributed Problem Solving

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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
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IntroductionSemantic Web - new Possibilities
for Intelligent Web Applications
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Motivation for Semantic Web
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Semantic Web Content New Users
applications
agents
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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
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Semantic Web Resource Integration
Semantic annotation
Shared ontology
Web resources / services / DBs / etc.
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What else Can be Annotated for Semantic Web ?
External world resources
Web resources / services / DBs / etc.
Web users (profiles, preferences)
Shared ontology
Web agents / applications
Web access devices
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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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University of Jyvaskyla ExperienceExamples of
Related Courses
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DAI Course Lectures
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Lecture 0 This Lecture - DAI Introduction
http//www.cs.jyu.fi/ai/vagan/DAI_Introduction.ppt

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Lecture 1 Web Content Personalization Overview
http//www.cs.jyu.fi/ai/vagan/Personalization.ppt
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Lecture 2 What is an Intelligent Agent ?
http//www.cs.jyu.fi/ai/vagan/Agents.ppt
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Lectures 3-4 Agent Technologies
http//www.cs.jyu.fi/ai/vagan/Agent_Technologies.p
pt
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Lecture 5 Collaborative Filtering
http//www.cs.jyu.fi/ai/vagan/Collaborative_Filter
ing.ppt
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Lecture 6 Introduction to Bayesian Networks
http//www.cs.jyu.fi/ai/vagan/Bayes_Nets.ppt
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Lecture 7 Dynamic Integration of Virtual
Predictors
http//www.cs.jyu.fi/ai/vagan/Virtual_Predictors.p
pt
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Lecture 8 Metamodels for Managing Knowledge
http//www.cs.jyu.fi/ai/vagan/Metamodels.ppt
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DAI Course Exercise
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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.

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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?

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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?

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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 3 to 5
  pages long.

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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 - 13 December 2002 (2400)
• Files with presentations should be sent by e-mail
  to Vagan Terziyan (vagan_at_it.jyu.fi)
• Notification of evaluation - until 14 December
  (1600).

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DAI Course Assignment
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Assignment in brief

• Students are expected to select one of below
  recommended papers, which is not already selected
  by some other student, register his/her choice
  from the Course Lecturer 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.

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Evaluation criteria for the assignment

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

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Format, Submission and Deadlines

• Format PowerPoint ppt. (winzip encoding
  allowed), name of file is students family name
• Presentation should contain all references to the
  materials used, including the original paper
• Deadline - 13 December 2002 (2400)
• Files with presentations should be sent by e-mail
  to Vagan Terziyan (vagan_at_it.jyu.fi)
• Notification of evaluation - until 14 December
  (1600).

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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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University of Jyvaskyla Experience Examples of
Course-Related Research
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Mobile Location-Based Service in Semantic Web
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Mobile Transactions Management in Semantic Web
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P-Commerce in Semantic Web
Terziyan V., Architecture for Mobile P-Commerce
Multilevel Profiling Framework, IJCAI-2001
International Workshop on "E-Business and the
Intelligent Web", Seattle, USA, 5 August 2001, 12
pp.
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Semantic Metanetwork for Metadata Management
Semantic Metanetwork is considered formally as
the set of semantic networks, which are put on
each other in such a way that links of every
previous semantic network are in the same time
nodes of the next network. In a Semantic
Metanetwork every higher level controls semantic
structure of the lower level.
Terziyan V., Puuronen S., Reasoning with
Multilevel Contexts in Semantic Metanetworks, In
P. Bonzon, M. Cavalcanti, R. Nossun (Eds.),
Formal Aspects in Context, Kluwer Academic
Publishers, 2000, pp. 107-126.
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Petri Metanetwork for Management Dynamics

• A metapetrinet is able not only to change the
  marking of a petrinet but also to reconfigure
  dynamically its structure
• Each level of the new structure is an ordinary
  petrinet of some traditional type.
• A basic level petrinet simulates the process of
  some application.
• The second level, i.e. the metapetrinet, is used
  to simulate and help controlling the
  configuration change at the basic level.

Terziyan V., Savolainen V., Metapetrinets for
Controlling Complex and Dynamic Processes,
International Journal of Information and
Management Sciences, V. 10, No. 1, March 1999,
pp.13-32.
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Bayesian Metanetwork for Management Uncertainty
Terziyan V., Vitko O., Bayesian Metanetworks for
Mobile Web Content Personalization, In
Proceedings of 2nd WSEAS International Conference
on Automation and Integration (ICAI02), Puerto
De La Cruz, Tenerife, December 2002.
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Multidatabase Mining based on Metadata
Puuronen S., Terziyan V., Logvinovsky A., Mining
Several Data Bases with an Ensemble of
Classifiers, In T. Bench-Capon, G. Soda and M.
Tjoa (Eds.), Database and Expert Systems
Applications, Lecture Notes in Computer Science,
Springer-Verlag, V. 1677, 1999, pp. 882-891.