parallel and distributed intelligent systems: multi-agent systems and e-commerce
DESCRIPTION
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 [email protected]. Outline. - PowerPoint PPT PresentationTRANSCRIPT
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Parallel and Distributed Intelligent Systems: Multi-Agent Systems and e-
Commerce
Virendrakumar C. BhavsarProfessor and
Director, Advanced Computational Research Laboratory
Faculty of Computer Science, University of New Brunswick Fredericton, NB, Canada
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OutlineOutline
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. MironovSpecification 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 ACORN (Agent-based Community Oriented Retrieval Network) ArchitectureRetrieval Network) Architecture
Steve Marsh, Steve Marsh, Institute for Information Technology, NRC Institute for Information Technology, NRC
Virendra C. Bhavsar, Ali A. Ghorbani, Virendra C. Bhavsar, Ali A. Ghorbani, UNBUNB
- Keyphrase-based Information Sharing between Agents- Keyphrase-based Information Sharing between Agents Hui Yu – MCS Thesis (UNB) Hui Yu – MCS Thesis (UNB) MATA’2000 Paper MATA’2000 Paper
- Performance Evaluation using Multiple Autonomous Virtual - Performance Evaluation using Multiple Autonomous Virtual Users Users HPCS’2000 paper HPCS’2000 paper
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ACORNACORN Agent-Based Community-Oriented {Retrieval | Agent-Based Community-Oriented {Retrieval |
Routing} NetworkRouting} NetworkACORN 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 SeparationDegrees of Separation
In the 1960’s, 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 don’t 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 WorkRelation to Other Work Search Engines
– Alta Vista, Excite, Yahoo, InfoSeek, Lycos, etc...– We don’t aim to search the Web – If the user has to search, it’s because the information diffusion is
not fast enough not accurate enough
Recommender Systems– Firefly (Maes), Fab (Balabanovic)– Content-based or Collaborative– ACORN’s 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.)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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ACORNACORN
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 AgentThe ACORN Mobile Agentrepresents a unit of informationstructure
Mobile AgentName: (Unique ID, timestamp)Owner Address
Dublin Core Metadata
Visited Recommended Known
Lists of users (humans) and/or cafésthe agent has visited, is due to visit,
or ‘knows of’
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The Dublin CoreThe 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 LifecycleAgent 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 RecommendationsThe 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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CaféCaféAt 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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Server
Server
Server
Server
Server
anwhere.else
cs.stir.ac.ukmeto.gov.uk
ucsd.eduai.it.nrc.ca
Clients
Café Café
Café
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Testing and DeploymentTesting and Deployment
A working implementation of ACORN in Sun’s 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 UsersMultiple 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
core’s interest
- migrates to other servers
- potential destinations
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Adaptation of ACORNAdaptation 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.)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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ExperimentsExperiments
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 WorkFuture 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 SystemsMulti-Agent SystemsB2B-B2C ExtensionsB2B-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 SystemsMulti-Agent SystemsB2B-B2C ExtensionsB2B-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 SystemsMulti-Agent SystemsB2B-B2C ExtensionsB2B-B2C Extensions
Adaptation to Multi-processor machines at a single as well as multiple sites to exploit CA*NETIII
Usability Studies XML objects instead of Java objects
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Trust In Information Systems - eCommerceTrust 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 - eCommerceTrust 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 Multi-Agent Systems for Distributed DatabasesDatabases
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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ConclusionConclusion
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.)