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

bhavsar@unb.ca

OutlineOutline

Past Research Work Current Research Work Multi-Agent Systems ACORN and Extensions Multi-Agent Systems and E-Commerce

Applications Areas for Collaboration Conclusion

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

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

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

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

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)

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

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.

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)

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)

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

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

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

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

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

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

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’

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

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

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)

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

Server

Server

Server

Server

Server

steve@ai.it.nrc.ca

ymasrour@ai.it.nrc.ca

bob@ai.it.nrc.ca

foo@anywhere.else

wibble@cs.stir.ac.uk

anne@cs.stir.ac.uk

graham@cs.stir.ac.uk

jane@meto.gov.uk

joan@meto.gov.uk

dick@ucsd.edu

tom@ucsd.edu

anwhere.else

cs.stir.ac.ukmeto.gov.uk

ucsd.eduai.it.nrc.ca

Clients

Café Café

Café

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

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

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

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

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

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

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,

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

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

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

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

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

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.)