Transcript Agent Technologies in Mobile Environment

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
[email protected] ; [email protected]
http://www.cs.jyu.fi/ai/vagan
+358 14 260-4618
Contents
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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:
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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.
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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 ?”
Ag. C134.1
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”
Ag. Auditorio 2
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. C233.1
Lecture 8 - ”SmartResource: Agent-Based Self-Managed Web Resources - II”
Monday lectures: 12:15 – 13:55; Break: 13:00 – 13:10; Place: Agora Alfa
Tuesday lectures: 10:15 – 11:55; Break: 11:00 – 11:10; 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
Place: Computer Class
Lab. work 3 - ” Development for SmartResource II”
15 May 2007
– Agent Design Lab - IV
Lab. work 4 - ” Development for SmartResource III”
Monday lectures: 12:15 – 13:55; Break: 13:00 – 13:10; Place: Agora Alfa
Tuesday lectures: 10:15 – 11:55; Break: 11:00 – 11:10; Place: Agora Alfa
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Course Motivation
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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.
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We believe that self-manageability of a complex system
requires its components to be autonomous themselves, i.e. be
realised as agents.
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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:
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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)
Proactive system design is
guided by seven
underlying principles:
“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)
• 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 serviceorientation.
 Componentization enables a business to operate in a value net, a
network of partnerships with customers and suppliers supported by realtime 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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TAPAS
The “Theatre” metaphor
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.
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Norwegian University of Science and Technology, Trondheim
Google: Excellent content and context
provider for Web applications
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Google Maps,
Google Earth,
Wikimapia,
GMail,
Blogger,
etc.
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Two alternative trends of Web development
Machines,
devices,
software, etc
Human
Communities
Facilitates
Human-to-Human
interaction
Facilitates Machineto-Machine
interaction
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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
Semantic Web Structure
Before Semantic Web
Semantic
Annotations
Ontologies
Logical Support
Languages
Tools
Applications /
Services
Semantic
Web
WWW
and
Beyond
Creators
Users
WWW
and
Beyond
Web content
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Creators
Users
Web content
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Semantic Web: New “Users”
Semantic
Web and
Beyond
Users
Creators
applications
Semantic Web
content
agents
Semantic
Annotations
Ontologies
Logical Support
Languages
Tools
Applications /
Services
Semantic
Web
WWW
and
Beyond
Creators
Users
Web content
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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 access devices and
communication networks
Smart
machines,
devices,
homes, etc.
Web agents /
applications /
software
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components
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 EcoSystem 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.
Human-to-Human
Human-to-Machine
Machine-to-Human
Machine-to-Machine
Agent-to-Agent
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Core technologies for GUN
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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
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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
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SmartResource – semantic technology, pilot tools and standards for UBIWARE
SmartResource in the IOG Web Site
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One of Smart Resource Scenarios
“Knowledge Transfer
from Expert to Service”
Agent plays roles:
“Expert”
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”
“Device”
Labelled
data
Labelled
data
“Service”
History
data
Agent plays roles:
Diagnostic
model
Scene 1: “patient”;
Scene 2: “teacher”;
Scene 3: “patient”
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Agent-driven EAI (1)
operator
field crew
expert
consumers owner
manager
administration
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Agent-driven EAI (2)
Sensors and
alarm detectors
Resource
info
Operators
Experts
Software and
services
AI tools
(Knowledge
Discovery)
Maintenance
workers
Other users
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Agents in mobile environment
Mobile
Customer
Mobile
Customer
Agent
(Peer)
Mobile
Customer
Agent
(Peer)
Agent
(Peer)
Agent
(Peer)
Mobile
Customer
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Agent-driven EAI in mobile environment
Call center
field crew
Expert/specialist
customers
manager
administration
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Agent-driven integration in mobile environment
Zone 1
Operating on
3G WWAN
Zone 2 3G WWAN
Wakeup Wi-Fi
Wi-Fi Link Going Down.
Connect to
Wi-Fi
Continue
session on Wi-Fi
Airport
Zone 6
Radio State
3G WWAN
Continue session
on 3G WWAN
Home
Battery level low
Shutdown WiMAX
Switch to 3G WWAN
Operator initiated switch to WiMAX
Continue session on WiMAX
Shutdown Wi-Fi
Zone 7
Plug into power jack
Wakeup Wi-Fi
Continue over Wi-Fi
Zone 5
Zone 4
Zone 3
WiMAX
Zone 8
WiMAX
Wi-Fi
WiMAX
GPS
Zone 9
IEEE 802.21, SIP, VCC, IMS, for Network Selection and Service
VCC, SIP,
for
Call
Continuity
WWAN

Wi-Fi)
802.21,
SIP,IMS
IMS
IEEE
for
802.21
Service
forContinuity
Network (3G
Discovery
(Wi-Fi
WiMAX)
Continuity across multiple radios (3G WWAN  Wi-Fi  WiMAX)34
Agent-driven peer-to-peer environments
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JADE-LEAP Agent Platform is extension to JADE
(special container within JADE)
Target devices
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Mikko Laukkanen
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
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Agent-Driven EAI (Human-Centric)
2
Online
Monitoring
Sensing
Testing
Diagnostics
Treatment
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3
1
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Word-Wide Correlated Activities
Semantic Web
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 is a global, collaborative effort
to construct an open network of on-line systems
hosting diverse agent based services.
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.
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
FIPA
FIPA is a non-profit organisation aimed
at producing standards for the interoperation
of heterogeneous software agents.
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Package of courses
Java programming,
AI basics
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
[email protected] ; [email protected]
http://www.cs.jyu.fi/ai/vagan
+358 14 260-4618
Spring
Fall
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
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Lecture 2: What is an Intelligent Agent ?
Ability to Exist to be Autonomous,
Reactive, Goal-Oriented, etc.
What is an Intelligent Agent ?
- are the basic abilities of an Intelligent Agent
Based on Tutorials:
Monique Calisti, Roope Raisamo
http://www.cs.jyu.fi/ai/vagan/Agents.ppt
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Lectures 3-4: Agent Technologies (Mobility,
Communication, Coordination, Negotiation)
Mobility and Flexibility, Abilities to Communicate,
Cooperate, and Negotiate with other Agents - are
among the basic abilities of an Intelligent Agent
Agent Technologies
Based on tutorials: Monique Calisti, Amund Tveit, Shaw Green, Leon Hurst,
Brenda Nangle, Pádraig Cunningham, Fergal Somers, Richard Evans
2
1
http://www.cs.jyu.fi/ai/vagan/Agent_Technologies.ppt
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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
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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
• 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
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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
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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
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Lecture 12: SmartResource Platform
• Architecture
• Script language (semantic APL)
• Developing Reusable Atomic
Behaviors (RABs)
http://people.cc.jyu.fi/~akataso/ties423/Lecture12.pdf
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ATME Course: Assignment
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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.
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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 ([email protected] and [email protected]);
 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
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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 email to Artem Katasonov ([email protected]).
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Information about Related Course
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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
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Additional Reading (2): Personalization in Mobile
Environment
http://www.cs.jyu.fi/ai/vagan/Mobile_Personalization.ppt
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