No name

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• 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

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Outline

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

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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

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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

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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

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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

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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)
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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

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• 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.

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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)
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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)

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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
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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

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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

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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

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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

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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

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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
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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

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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

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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)

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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

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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
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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

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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

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Adaptation of ACORN

• ACORN 100 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

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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

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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

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Future Research Work

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

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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,

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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

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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

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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

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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

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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

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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.)