- PowerPoint PPT Presentation

About This Presentation
Title:

Description:

Parallel and Distributed Intelligent Systems: Multi-Agent Systems and e-Commerce Virendrakumar C. Bhavsar Professor and Director, Advanced Computational Research ... – PowerPoint PPT presentation

Number of Views:44
Avg rating:3.0/5.0
Slides: 40
Provided by: Virendra
Category:

less

Transcript and Presenter's Notes

Title:


1
 
  • Parallel and Distributed Intelligent Systems
    Multi-Agent Systems and e-Commerce
  • Virendrakumar C. Bhavsar
  • Professor and
  • Director, Advanced Computational Research
    Laboratory
  • Faculty of Computer Science, University of New
    Brunswick Fredericton, NB, Canada
  • bhavsar_at_unb.ca

2
Outline
  • Past Research Work
  • Current Research Work
  • Multi-Agent Systems
  • ACORN and Extensions
  • Multi-Agent Systems and E-Commerce Applications
  • Areas for Collaboration
  • Conclusion

3
Past Research Work
  • B. Eng. (Electronics and Telecommunications)
  • University of Poona, India
  • Project 4-Bit Calculator
  • M.Tech. (Electrical Eng. - specialization
    Instrumentation, Control, and Computers)
  • Indian Institute of Technology, Bombay, India
  • Thesis Special Purpose Computers for Military
    Applications with Emphasis on Digital
    Differential Analysers (DDAs)
  • ? Ph. D. (Electrical Eng.)
  • Indian Institute of Technology, Bombay, India
  • Parallel Algorithms for Monte Carlo Solutions of
    Linear Operator Problems

4
Past Research Work
  • ? Parallel/Distributed Processing
  • - Parallel Computer Architecture
  • Design and Analysis of Parallel Algorithms for
  • Monte Carlo Methods, Pattern Recognition,
  • Computer Graphics, Artificial Neural Networks,
  • Computational Physics, and other applications
  • Real-time and Fault-Tolerant Systems
  • for Process Control and On-Board Applications
  • ? Artificial Neural Networks
  • - with Dr. Ghorbani
  • ? Learning Machines and Evolutionary
  • Computation
  • - with Dr. Ghorbani and Dr. Goldfarb

5
Past Research Work
  • Computer Graphics (with Prof. Gujar)
  • Modeling of 3-D Solids
  • Generation and Rendering of Interpolated Objects
  • Algebraic and Geometric Fractals
  • Parallelization of Computer Graphics Algorithms
  • Visualization (with Dr. Ware)
  • PVMtrace Visualization of Parallel and
    Distributed
  • Programs

6
(No Transcript)
7
(No Transcript)
8
Past Research Work
  • ? Multimedia for Education
  • Intelligent Tutoring Systems for Discrete
    Mathematics
  • ( a NCE TeleLearning Project)
  • with Dr. Jane Fritz and Prof. Uday Gujar
  • - Animated Computer Organization
  • Multi-Lingual Systems and Transliteration
  • Web Portal for an NB company
  • Clustifier and Extractor
  • Intelligent User Profile Generator
  • ? Supervision/co-supervision
  • - 50 master's theses - 4 doctoral theses
  • - 5 post-doctoral fellows/research
    associates

9
Current Research Work
? Bioinformatics -Canadian Potato Genomics
Project - databases, multi-agent systems, pattern
recognition ? Parallel/Distributed
Processing - C3-Grid development Design and
analysis of parallel/distributed
applications Dr. Aubanel (Research
Associate)
10
Current Research Work
? Multi-Agent Systems - with Dr. Ghorbani and
Dr. Marsh (NRC, Ottawa) - Intelligent
agents - Keyphrase-based Information sharing
between agents - Scalability and Performance
Evaluation - Applications to e-commerce and
bioinformatics - with Dr. Mironov Specification
and verification of multi-agent systems

11
  • Advanced Computational Research Laboratory (ACRL)
  • Dr. Virendra Bhavsar (Director)
  • Dr. Eric Aubanel (Research Associate)
  • Mr. Sean Seeley (Technical Support)
  • ACRL Management Committee
  • AC3 Atlantic Canada High Performance
  • Computing Consortium
  • C3.ca Association Inc.

12
ARCL
Advanced Computational Research Laboratory ?
High Performance Computational Problem-Solving
Environment and Visualization Environment ?
Computational Experiments in multiple
disciplines Computer Science, Science and
Engineering ? Located in the Information
Technology Center (ITC)
13

14
ACRL Facilities
? High Performance Multiprocessor
(16-processor) System - 24 GFLOPS (peak)
performance - 72 GB internal disk storage - 109.2
GB external disk storage ? Software for
Computational Studies and Visualization ?
Parallel Programming Tools ? E-Commerce
Software, including datamining software ?
Memorandum of Understanding between IBM and UNB
(in process)

15
ACORN (Agent-based Community Oriented
Retrieval Network) ArchitectureSteve Marsh,
Institute for Information Technology, NRC
Virendra C. Bhavsar, Ali A. Ghorbani, UNB-
Keyphrase-based Information Sharing between
Agents Hui Yu MCS Thesis (UNB) MATA2000
Paper- Performance Evaluation using Multiple
Autonomous Virtual Users HPCS2000
paper
16
ACORN Agent-Based Community-Oriented
Retrieval Routing Network
  • ACORN is a multi-agent based system for
    information diffusion and (limited) search in
    networks
  • In ACORN, all pieces of information are
    represented by semi-autonomous agents...-
    searches documents images, etc.
  • Intended to allow human users to collaborate
    closely

17
Degrees of Separation
  • In the 1960s, Stanley Milgram showed that
    everyone in the US was personally removed from
    everyone else by at most six degrees of
    separation
  • In communities, such as a research community,
    this is clear to all members
  • if you want to know something, you ask someone.
  • If they dont know, they may know someone else to
    ask...
  • and so on
  • This also works when you have something to tell
    people...
  • if you want someone relevant to know, you tell
    people you know will be interested...
  • and they forward the information to people they
    know will be interested..
  • and so on

18
Relation to Other Work
  • Search Engines
  • Alta Vista, Excite, Yahoo, InfoSeek, Lycos,
    etc...
  • We dont aim to search the Web
  • If the user has to search, its because the
    information diffusion is
  • not fast enough
  • not accurate enough
  • Recommender Systems
  • Firefly (Maes), Fab (Balabanovic)
  • Content-based or Collaborative
  • ACORNs agents are a radical new approach, and a
    mixture of both...
  • ACORN is distributed
  • ACORN levers direct human-human contact knowledge
  • Matchmakers
  • Yenta (Foner)
  • Very close to the ACORN spirit, lacking in
    flexibility of ACORN

19
Relation to Other Work (cont.)
  • Web Page Watchers and Push Technologies
  • Tierra, Marimba, Channels
  • ACORN is a means of pushing new data, reducing
    the need to watch for changes
  • Filtering Systems
  • The filtering in ACORN is implicit in what is
    recommended by humans
  • Knowbots
  • Softbots (Washington, Etzioni, Weld), Nobots
    (Stanford, Shoham)
  • mobile agents for internet search
  • ACORN provides diffusion also

20
ACORN
  • Uses communication between agents representing
    pieces of information, ACORN automates some of
    the processes
  • Anyone can create agents, and direct them to
    parties they know will be interested
  • An Agent carries user profile
  • Agents can share information

21
The ACORN Mobile Agent
  • represents a unit of information
  • structure

Mobile Agent Name (Unique ID, timestamp) Owner
Address Dublin Core Metadata Visited Recommende
d Known
Lists of users (humans) and/or cafés the agent
has visited, is due to visit, or knows of
22
The Dublin Core
  • The Dublin Core is a Metadata element set, first
    developed at a workshop in Dublin, Ohio
  • Includes author, title, date
  • Also includes
  • Keywords Publisher type (e.g. home page, novel,
    poem)
  • format (of data)
  • The Dublin Core presents a powerful structured
    medium for distributing human (and machine)
    readable metadata
  • It also presents an interesting query formulation
    tool
  • The DC home page can be found at http//purl.org
    /metadata/dublin_core

23
Agent Lifecycle
  • A mobile agent in ACORN (one which represents
    information) undergoes several stages in its
    lifecycle
  • Creation
  • Distribution
  • Visiting a user
  • Mingling with other agents
  • Going to next site
  • Return

24
The Café - Agent Recommendations
  • User recommendations are not the only way an
    agent can expand its list of people to visit
  • Each site can have (between zero and many) cafés
  • A café is simply a meeting place for agents
  • Cafés can be generic or have specific topics
    (agents can be filtered before entering)

25
Café
  • At set intervals, agents present are compared,
    and relevant information exchanged
  • Keyphrase-based Information Sharing
  • Agents reside at cafés for set lengths of time
    (currently we have a default, but intend to make
    the length of time owner selectable)
  • The café represents a unique method of automating
    community based information sharing

26
tom_at_ucsd.edu
ucsd.edu
ymasrour_at_ai.it.nrc.ca
ai.it.nrc.ca
S e r v e r
bob_at_ai.it.nrc.ca
dick_at_ucsd.edu
steve_at_ai.it.nrc.ca
anwhere.else
foo_at_anywhere.else
cs.stir.ac.uk
meto.gov.uk
joan_at_meto.gov.uk
Clients
jane_at_meto.gov.uk
wibble_at_cs.stir.ac.uk
graham_at_cs.stir.ac.uk
anne_at_cs.stir.ac.uk
27
Testing and Deployment
  • A working implementation of ACORN in Suns Java
    language
  • Stress testing the architecture using large
    numbers of real users - problems
  • Multiple artificial users on a simulated network

28
Multiple Autonomous Virtual Users
  • Test-bed Several Autonomous Servers, each
    serving autonomous virtual users
  • Virtual User - capable of creating agents
  • - picks up a topic from
    a client
  • cores interest
  • - migrates to other
    servers
  • - potential destinations

29
Adaptation of ACORN
  • ACORN gt100 Java classes
  • Adaptation
  • Removal of user interaction classes
  • Removal of client behavior clases
  • Removal of other extraneous classes
  • Simulation of multiple client-server
    architecture run more than one server on a
    single machine
  • Possibility of using multiple processor machines
  • Addition of a SiteController Class

30
Adaptation of ACORN (cont.)
  • SiteController Class
  • handles all communication between servers on a
    single machine
  • resolves agent migration requests
  • handles communication between different machines
  • Streamer Class
  • provides transport of agents across IP
  • Benefits
  • Removal of the need for continuous user
    interaction
  • Batch mode runs
  • Only 30 Java classes

31
Experiments
  • Virtual Users
  • Porting of ACORN to many machine architectures
  • SGI Onyx. PowerPC, and PC
  • O(n2) agent interactions in a Café, n - number of
    agents

32
Future Research Work
  • ? Bioinformatics
  • -Canadian Potato Genomics Project
  • Biological databases, multi-agent systems,
    pattern recognition
  • Multi-Agent Systems - ACORN and B2B B2C
    extensions

33
Multi-Agent SystemsB2B-B2C Extensions
  • ACORN and B2B B2C extensions
  • - User-driven personalisation
  • personalised and personalisable automatic
    delivery and search for information
  • directed advertisements based on user profiles
    and preferences
  • directed programming (both these examples based
    on interactive TV facilities such as those
    offered by iMagicTV and Microsoft interactive
    TV).
  • agent learning
  • data mining over large distributed networks and
    databases,

34
Multi-Agent SystemsB2B-B2C Extensions
  • ACORN and B2B B2C extensions
  • - the management of firms and user reputation
    (as in eBay's reputation manager, amongst others)
  • ? finally leading into proposed standards and
    legal bases necessary for eCommerce
  • Perceived and actual user privacy
  • Automated and manually-driven user profile
    generation and update

35
Multi-Agent SystemsB2B-B2C Extensions
  • Adaptation to Multi-processor machines at a
    single as well as multiple sites to exploit
    CANETIII
  • Usability Studies
  • XML objects instead of Java objects

36
Trust In Information Systems - eCommerce
  • Formalization of Trust Steve Marsh (early 1990s)
  • Prototype version of an adaptable web site for
    eCommerce transactions
  • Trust in information systems
  • - creation and sustainability
  • - user interface technologies
  • - user perceptions, behaviors, etc. and
    how to
  • influence and use such user behaviors.
  • - automatic user profile generation, its use in
    agent-based interfaces such as the trust
    reasoning adaptive web sites

37
Trust In Information Systems - eCommerce
  • Adaptive technologies in general for eCommerce,
    education, entertainment
  • Personality in the user interface and how it can
    affect user trust and perceived satisfaction

38
Multi-Agent Systems for Distributed Databases
  • Problem Businesses are faced with continuous
    updating of their large and distributed databases
    connected on intranets and the Internet
  • Multi-Agent Systems
  • - Very naturally satisfiy many requirements in
    such an environment
  • - Provide a very flexible and open
    architecture
  • - Scalability analysis with multiprocessor
    servers

39
Conclusion
  • Parallel and Distributed Intelligent Systems
  • Multi-Agent Systems and ACORN
  • Applications in e-Commerce
  • B2B and B2C Extensions
  • Trust in Information Systems
  • Multi-Agent Systems for Distributed Databases
  • NRC Collaborations in the above and other areas
    (Software Engineering, Intelligent Systems, etc.)
Write a Comment
User Comments (0)
About PowerShow.com