University of Jyvaskyla

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12 Νοε 2013 (πριν από 3 χρόνια και 5 μήνες)

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TIES
-
423
(TLI363)



Agent Technologies in Mobile Environment


former name:

TLI371


Distributed Artificial Intelligence in Mobile Environment


Course Introduction

Vagan Terziyan

Department of Mathematical Information Technology

University of Jyvaskyla


vagan@it.jyu.fi ; terziyan@yahoo.com

http://www.cs.jyu.fi/ai/vagan

+358 14 260
-
4618

2

Contents


Course Introduction


Lectures and Links


Course Assignment


Course Exercise

3

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 (24:00)
;


Exam: There will be
no exam
. Course grade will be given based on the exercise
and assignment quality.

4

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




Lecture 8
-

”SmartResource: Agent
-
Based Self
-
Managed Web Resources
-

II”

Tuesday lectures:
10:15


11:55
; Break:
11:00


11:10
; Place: Agora
Alfa

Monday lectures:
12:15


13:55
; Break:
13:00


13:10
; Place: Agora
Alfa

Ag. Auditorio 2

Ag. C134.1

Ag. C233.1

5

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”

Tuesday lectures:
10:15


11:55
; Break:
11:00


11:10
; Place: Agora
Alfa

Monday lectures:
12:15


13:55
; Break:
13:00


13:10
; Place: Agora
Alfa

Place: Computer Class

6

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

7

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.


8

INTEL:
Proactive Computing Concept (2)

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.

“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 today’s
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)

9

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.

10

IBM:
Autonomic Computing (2)

11

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)...”

12

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.

13

The

Theatre


metaphor


Theatre:

A metaphor for concepts and functionality definition.

Director role figure
: The manager of plays, and
supervisor for application role figures, constituted
by an
actor
.

Repertoire:

The set of
Plays

that may be performed
at the theatre.

Application role figures
: The performers of plays.
Constituted by
actors

playing
roles
.

Play
: Defines a set of logically related functionality.

Capability
: A unique set of properties of an
actor
at
the stage where he is playing.

Manuscript
: The assigned behavior, i.e. the defined
role

of a
role figure
, constituted by an an
actor
.

Role session
: A dialogue between two
role figures
.

Actors

TAPAS

Norwegian University of Science and Technology, Trondheim

14

Google: Excellent content and context
provider for Web applications


Google Maps,


Google Earth,


Wikimapia,


GMail,


Blogger,


etc.

15

Two alternative trends of Web development

Human
Communities

Machines,
devices,
software, etc

Facilitates
Human
-
to
-
Human
interaction

Facilitates Machine
-
to
-
Machine
interaction

16

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.

17

Sample of Wiki Web page

Collaborative
editing window

18

Wikipedia

19

Web 2.0 Community Portal

20

Motivation for Semantic Web

7
Before Semantic Web
Web content
Users
Creators
WWW
and
Beyond
8
Semantic Web Structure
Semantic
Annotations
Ontologies
Logical Support
Languages
Tools
Applications /
Services
Web content
Users
Creators
WWW
and
Beyond
Semantic
Web
21

Semantic Web: New “Users”

Semantic
Annotations
Ontologies
Logical Support
Languages
Tools
Applications /
Services
Web content
Users
Creators
WWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications

agents

22

Semantic Web: Resource Integration

Shared
ontology

Web resources /
services / DBs / etc.

Semantic
annotation

23

Shared
ontology

Web users
(profiles,
preferences)

Web access devices and
communication networks

Web agents /
applications /
software
components

External world
resources

Smart
machines,
devices,
homes, etc.

Technological
and business
processes

Semantic Web: which resources to annotate ?

Multimedia
resources

Web resources /
services / DBs / etc.

This is just a small part of
Semantic Web concern !!!

Semantic
annotation

24

GUN Concept

GUN



G
lobal
U
nderstanding
e
N
vironment


GUN

=

Global Environment

+

Global Understanding

=

Proactive Self
-
Managed

Semantic Web of Things

= (
we believe
) =


Killer Application
” for
Semantic Web Technology


25

GUN and Ubiquitous Society

Human
-
to
-
Human

Human
-
to
-
Machine

Machine
-
to
-
Human

Machine
-
to
-
Machine

Agent
-
to
-
Agent

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.

26

Core technologies for GUN


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

27

GUN
-
GERI
-
UBIWARE
-
SmartResource ?

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

http://www.cs.jyu.fi/ai/OntoGroup/projects.htm

28

SmartResource in the IOG Web Site

29

One of Smart Resource Scenarios

“Expert”

“Service”

Labelled
data

Labelled
data

Diagnostic
model

History
data

“Device”

“Knowledge Transfer
from Expert to Service”

Agent plays roles:


Scene 1: “
patient
”;

Scene 2: “
teacher
”;

Scene 3: “
patient


Agent plays roles:


Scene 1: “
diagnostic expert
”;

Scene 2: “
no play
”;

Scene 3: “
no play


Agent plays roles:


Scene 1: “
no play
”;

Scene 2: “
student
”;

Scene 3: “
diagnostic expert


30

field crew

operator

expert

consumers

owner

manager

administration

Agent
-
driven EAI (1)

31

Operators

Experts

Software and
services

Maintenance
workers

AI tools
(Knowledge
Discovery)

Sensors and
alarm detectors

Other users

Resource
info

Agent
-
driven EAI (2)

32

Mobile
Customer
Agent
(Peer)
Agent
(Peer)
Agent
(Peer)
Agent
(Peer)
Mobile
Customer
Mobile
Customer
Mobile
Customer
Agents in mobile environment

33

field crew

Call center

Expert/specialist

customers

manager

administration

Agent
-
driven EAI in mobile environment

34

3G WWAN

Home

Airport

Zone 1

Zone 2

Zone 3

Zone 4

Zone 5

Zone 6

Zone 7

Zone 9

WiMAX

Zone 8

WiMAX

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

Radio State

3G WWAN

Wi
-
Fi

WiMAX

GPS

IEEE 802.21 for Network Discovery

IEEE 802.21, SIP, VCC, IMS, for Network Selection and Service
Continuity across multiple radios (3G WWAN



-
䙩F


W楍i堩

㠰㈮2ㄬ1卉SⰠ䥍匠景爠卥牶楣i 䍯湴楮畩瑹††⡗
-
䙩F


W楍i堩

噃VⰠ卉SⰠ䥍匠景爠䍡汬⁃潮瑩t畩瑹†† †⠳䜠块A丠



-
䙩F

Plug into power jack
Wakeup Wi
-
Fi

Continue over Wi
-
Fi

Wi
-
Fi Link Going Down.

Operator initiated switch to WiMAX

Continue session on WiMAX

Shutdown Wi
-
Fi

Connect to
Wi
-
Fi

Battery level low

Shutdown WiMAX

Switch to 3G WWAN

Wakeup Wi
-
Fi

Continue
session on Wi
-
Fi

Operating on

3G WWAN

Continue session
on 3G WWAN

Agent
-
driven integration in mobile environment

35

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

36

Agent
-
Driven EAI (Human
-
Centric)

Sensing

Online
Monitoring

Testing

Diagnostics

Treatment

3

1

2

4

37

Word
-
Wide Correlated Activities

Semantic Web

Grid Computing

Web Services

Agentcities

Agentcities is a global, collaborative effort


to construct an open network of on
-
line systems


hosting diverse agent based 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

FIPA

FIPA is a non
-
profit organisation aimed


at producing standards for the interoperation


of heterogeneous software agents.

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

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.

38

TIES429
:
Semantic Web and Web Services
(same as TLI364)
former name:
TLI372

Intelligent Information Integration in Mobile Environment
Course Introduction
Vagan Terziyan
Department of Mathematical Information Technology, University of
Jyvaskyla
vagan@it.jyu.fi ; terziyan@yahoo.com
http://
www.cs.jyu.fi/ai/vagan
+358 14 260
-
4618
Package of courses


Spring

Fall

Java programming,
AI basics

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.ppt


41

Lecture 2:
What is an Intelligent Agent ?

http://www.cs.jyu.fi/ai/vagan/Agents.ppt



Ability to Exist to be Autonomous,
Reactive, Goal-Oriented, etc.
- are the basic abilities of an Intelligent Agent

What is an Intelligent Agent ?
Based on Tutorials:
Monique Calisti
,
Roope Raisamo

42

Lectures 3
-
4:
Agent Technologies

(Mobility,
Communication, Coordination, Negotiation)

http://www.cs.jyu.fi/ai/vagan/Agent_Technologies.ppt



2
Mobility and Flexibility, Abilities to Communicate,
Cooperate
, and Negotiate with other Agents
-
are
among the basic abilities of an Intelligent Agent

1
Agent Technologies
Based on tutorials:
Monique Calisti,
Amund Tveit
,

Shaw Green, Leon Hurst,
Brenda
Nangle
,
P
á
draig
Cunningham, Fergal
Somers
, Richard Evans
43

Lectures 5
-
6:
Agent Intelligence

(Internal Logic,
Reasoning, Planning, Learning, Knowledge Discovery)

http://www.cs.jyu.fi/ai/vagan/Agent_Intelligence.ppt


44

Lectures 7
-
8:
Industrial Applications of Agent Technology:
SmartResource

-

Agent
-
Based Self
-
Managed Web Resources

http://www.cs.jyu.fi/ai/vagan/SmartResource_Summary.ppt


45

Lecture 9:
Agents as a Novel Software Engineering
Paradigm

http://people.cc.jyu.fi/~akataso/ties423/Lecture9.pdf




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

46

Lecture 10:
Agent Platforms

http://people.cc.jyu.fi/~akataso/ties423/Lecture10.pdf




FIPA (IEEE) architecture



Existing platforms:



JADE



Cougaar



AgentFactory



3APL



Jason (AgentSpeak APL)



SmartResource Platform

47

Lecture 11:
Introduction to JADE

http://people.cc.jyu.fi/~akataso/ties423/Lecture11.pdf



Architecture



System agents and their GUIs



Main classes (Agent, Behaviour)
and their abilities

http://www.cs.jyu.fi/ai/vagan/JADE_Agents.ppt

see also:

48

Lecture 12:
SmartResource Platform

http://people.cc.jyu.fi/~akataso/ties423/Lecture12.pdf



Architecture



Script language (semantic APL)



Developing Reusable Atomic
Behaviors (RABs)

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 student’s family
name;


Presentation should contain all references to the materials
used, including the original paper;


Deadline
-

31 May 2007 (24:00);


Files with presentations should be sent by e
-
mail to Vagan
Terziyan (
vagan@it.jyu.fi
and

artem.katasonov@jyu.fi
);


Notification of evaluation
-

until 10 June.

53

Papers for Course Assignment (1)


Paper 1:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_1_P.pdf


Paper 2:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_2_P.pdf


Paper 3:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_3_CF.pdf


Paper 4:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_4_CF.pdf


Paper 5:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_5_MW.pdf


Paper 6:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_6_BN.pdf


Paper 7:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_7_BN.pdf


Paper 8:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_8_MM.pdf

54

Papers for Course Assignment (2)


Paper 9:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_9_WM.pdf


Paper 10:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_10_WM.pdf


Paper 11:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_11_III.pdf


Paper 12:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_12_III.pdf


Paper 13:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_13_KM.pdf


Paper 14:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_14_ES.pdf


Paper 15:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_15_MDB.pdf


Paper 16:

http://www.cs.jyu.fi/ai/vagan/course_papers/Paper_16_MDB.pdf

55

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 (24:00);


Source files and minimal documentation should be sent by e
-
mail to Artem Katasonov (artem.katasonov@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.


58

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_Personalization.ppt