TIES-423 (TLI363) – Agent Technologies in Mobile Environment former name:

TLI371 – Distributed Artificial Intelligence in Mobile Environment

Course Introduction

Vagan TerziyanDepartment 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

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Contents

Course IntroductionLectures and LinksCourse AssignmentCourse 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 (24:00); Exam: There will be no examno 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 AgentsLecture 2 - ”What is an Intelligent Agent ?”

19 March 2007 – Overview of (Multi)Agent Technologies - ILecture 3 - ”Agent Technologies - I”

20 March 2007 – Overview of (Multi)Agent Technologies - IILecture 4 - ”Agent Technologies - II”

26 March 2007 – Agent Intelligence – ILecture 5 - ” Agent Logic, Reasoning and Planning”

27 March 2007 – Agent Intelligence – IILecture 6 - ” Agent Learning and Knowledge Discovery”

2 April 2007 – Industrial Applications of Agent Technology - ILecture 7 - ”SmartResource: Agent-Based Self-Managed Web Resources - I”

3 April 2007 – Industrial Applications of Agent Technology - IILecture 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

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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 ProgrammingLecture 11 - ”Introduction to JADE”

24 April 2007 – Development with SmartResource Platform

Lecture 12 - ”SmartResource Platform”

7 May 2007 – Agent Design Lab - ILab. work 1 - ”Getting started with JADE”

8 May 2007 – Agent Design Lab - IILab. work 2 - ”Development for SmartResource I”

14 May 2007 – Agent Design Lab - IIILab. work 3 - ” Development for SmartResource II”

15 May 2007 – Agent Design Lab - IVLab. 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

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Course MotivationCourse 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: 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: 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)

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IBM: Autonomic Computing (1)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)IBM: Autonomic Computing (2)

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IBM: Service-Oriented Architecture (1)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)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 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

TAPASTAPAS

Norwegian University of Science and Technology, TrondheimNorwegian University of Science and Technology, Trondheim

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Google: Excellent content and context provider for Web applicationsGoogle: 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 developmentTwo alternative trends of Web developmentHuman

Communities

Machines, devices,

software, etc

Facilitates Human-to-Human

interaction

Facilitates Machine-to-Machine interaction

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What is WikiWhat 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 pageSample of Wiki Web page

Collaborative editing window

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WikipediaWikipedia

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Web 2.0 Community PortalWeb 2.0 Community Portal

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Motivation for Semantic Web

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Web Limitations

Doubles in sizeevery six months

Average WWW searches examineonly about 25% of potentially

relevant sites and return a lot ofunwanted information

Information on web is not suitablefor software agents

World Wide Web

Semantic Web

The Semantic Web is avision: the idea of havingdata on the Web defined andlinked in a way that it can beused by machines not just fordisplay purposes, but forautomation, integration andreuse of data across variousapplications.

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B e f o r e S e m a n t i c W e b

W e b c o n t e n t

U s e r sC r e a t o r sW W Wa n dB e y o n d

8

S e m a n tic W e b S tru c tu re

S e m a n ticA n n o ta tio n s

O n to lo g ie s L o g ic a l S u p p o rt

L a n g u a g e s T o o ls A p p lic a tio n s /S e rv ic e s

W e b c o n te n t

U se rsC re a to rsW W Wa n dB e y o n d

S e m a n ticW e b

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Semantic Web: New “Users”

SemanticAnnotations

Ontologies Logical Support

Languages Tools Applications /Services

Web content

UsersCreatorsWWWandBeyond

SemanticWeb

Semantic Webcontent

UsersSemanticWeb andBeyond

Creators

applications

agents

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Semantic Web: Resource Integration

Shared ontology

Web resources / services / DBs / etc.

Semantic annotation

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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 ?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

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GUN ConceptGUN ConceptGUN – 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 SocietyGUN 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.

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Core technologies for GUNCore 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

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GUN-GERI-UBIWARE-SmartResource ?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

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SmartResource in the IOG Web SiteSmartResource in the IOG Web Site

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One of Smart Resource ScenariosOne of Smart Resource Scenarios

““Expert”Expert”

““Service”Service”

Labelled data

Labelled data

Diagnostic model

Que

ryin

g di

agno

stic

Que

ryin

g di

agno

stic

resu

ltsre

sults

Labelled data

Labelled data

Wat

chin

g a

nd

qu

eryi

ng

dia

gn

ost

ic d

ataLa

belle

d da

ta

Labe

lled

data

History data

““Device”Device”

Querying data for

learning

Learning sample and

Learning sample and

Querying diagnostic results

Querying diagnostic results

““Knowledge Transfer Knowledge Transfer from Expert to Service”from Expert to Service”““Knowledge Transfer Knowledge Transfer

from Expert to Service”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”

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field crewoperator expert consumers owner manager administration

Agent-driven EAI (1)Agent-driven EAI (1)

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Operators ExpertsSoftware and

servicesMaintenance

workers

AI tools (Knowledge Discovery)

Sensors and alarm detectors

Other usersResource

info

Agent-driven EAI (2)Agent-driven EAI (2)

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MobileCustomer

Agent(Peer)

Agent(Peer)

Agent(Peer)

Agent(Peer)

M obileC ustom er

M obileC ustom er

M obileC ustom er

Agents in mobile environmentAgents in mobile environment

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field crewCall center Expert/specialist customers manager administration

Agent-driven EAI in mobile environmentAgent-driven EAI in mobile environment

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3G WWAN3G WWAN

HomeHome

AirportAirport

Zone 1 Zone 2 Zone 3

Zone 4 Zone 5 Zone 6

Zone 7 Zone 9WiMAXWiMAX Zone 8 WiMAXWiMAX

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

Radio StateRadio State

3G WWAN

Wi-Fi

WiMAX

GPS

IEEE 802.21 for Network DiscoveryIEEE 802.21 for Network DiscoveryIEEE 802.21 for Network DiscoveryIEEE 802.21 for Network DiscoveryIEEE 802.21, SIP, VCC, IMS, for Network Selection and Service IEEE 802.21, SIP, VCC, IMS, for Network Selection and Service Continuity across multiple radios (3G WWAN Continuity across multiple radios (3G WWAN Wi-Fi Wi-Fi WiMAX) WiMAX)

IEEE 802.21, SIP, VCC, IMS, for Network Selection and Service IEEE 802.21, SIP, VCC, IMS, for Network Selection and Service Continuity across multiple radios (3G WWAN Continuity across multiple radios (3G WWAN Wi-Fi Wi-Fi WiMAX) WiMAX)802.21, SIP, IMS for Service Continuity (Wi-Fi 802.21, SIP, IMS for Service Continuity (Wi-Fi WiMAX) WiMAX)802.21, SIP, IMS for Service Continuity (Wi-Fi 802.21, SIP, IMS for Service Continuity (Wi-Fi WiMAX) WiMAX)VCC, SIP, IMS for Call Continuity (3G WWAN VCC, SIP, IMS for Call Continuity (3G WWAN Wi-Fi) Wi-Fi)VCC, SIP, IMS for Call Continuity (3G WWAN VCC, SIP, IMS for Call Continuity (3G WWAN Wi-Fi) Wi-Fi)

Plug into power jack Wakeup Wi-FiContinue over Wi-Fi

Wi-Fi Link Going Down.

Operator initiated switch to WiMAXContinue session on WiMAXShutdown Wi-Fi

Connect to Wi-Fi

Battery level lowShutdown WiMAXSwitch 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 environmentAgent-driven integration in mobile environment

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Agent-driven peer-to-peer environmentsAgent-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)Agent-Driven EAI (Human-Centric)

Sensing Online Monitoring

Testing Diagnostics Treatment

3 1

2

4

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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 currentweb in which information is given well-definedmeaning, 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.

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TIES-423 (TLI363) – Agent Technologies in Mobile Environmentformer name:

TLI371 – Distributed Artificial Intelligence in Mobile Environment

Course Introduction

Vagan TerziyanDepartment 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

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

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ATME Course: Lectures

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Lecture 1: This Lecture - ATME Introduction

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

TLI363 –Agent Technologies in Mobile Environmentformer name:

TLI371 –Distributed Artificial Intelligence in Mobile Environment

Course Introduction

Vagan TerziyanDepartment 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

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, Pádraig Cunningham, Fergal Somers, Richard Evans

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Lectures 5-6: Agent Intelligence (Internal Logic, Reasoning, Planning, Learning, Knowledge Discovery)

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

Agent Intelligence

Based on tutorials and presentations:J.H. Siekmann, N. Nillson, S.J. Russel, P. Norvig, A. Geyer-

Schulz, C.Dyer, J. Robin, J. Han, C. Isik, M. Kamber, A. Logvinovskiy, S. Puuronen, V. Terziyan

Intelligent perception of the external environment, mining data and discovering knowledge about it, reasoning new facts about it, planning own behavior within it and acting based on plans - are among the basic abilities of an intelligent agent

Knowledge and factsAgent

Environment

Behavior

Plans

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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

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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

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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

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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:

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Lecture 12: SmartResource Platform

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

• Architecture

• Script language (semantic APL)

• Developing Reusable Atomic Behaviors (RABs)

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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.

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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.

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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

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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

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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 (24:00); Source files and minimal documentation should be sent by e-

mail to Artem Katasonov (artem.katasonov@jyu.fi).

57

Information about Related CourseAgent Technologies in the Semantic Webhttp://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

2

Discovering Casual Relationship from the Dynamic

Environmental Data and Managing Uncertainty - areamong the basic abilities of an intelligent agent

Casual networkwith Uncertainty

DynamicEnvironment

beliefs

Introductionto Bayesian Networks

Based on the Tutorials and Presentations:Based on the Tutorials and Presentations:(1) Dennis M.(1) Dennis M. Buede Buede Joseph A. Joseph A. Tatman Tatman, Terry A. , Terry A. BresnickBresnick;;(2) Jack(2) Jack Breese Breese and Daphne and Daphne KollerKoller;;(3) Scott Davies and Andrew Moore;(3) Scott Davies and Andrew Moore;(4) Thomas Richardson(4) Thomas Richardson(5) (5) Roldano CattoniRoldano Cattoni(6) (6) Irina Irina RichRich

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

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Additional Reading (2): Personalization in Mobile Environment

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

Personalisation in Mobile Environment

Based on papers and presentations of Catholijn Jonker, Vagan Terziyan, Jan Treur, Oleksandra Vitko and others

MIT Department, University of Jyväskylä