1. Multi-Agent Systems for e-Commerce Virendra C. Bhavsar Professor and Director, Advanced Computational Research Laboratory Faculty of Computer Science, University of New Brunswick Fredericton, NB, Canada bhavsar@unb.ca

2. Outline Multi-Agent Systems Multi-Agent Systems and E-Commerce Applications ACORN and Extensions Areas for Collaboration Conclusion

3. Agents “A software agent is an interface that looks like a person, acts like a person and even appears to think like one” “An agent has mental properties, such as knowledge, belief, intention and obligation.” In addition, it may have mobility, rationality, …

4. Multi-Agent Systems for e-Commerce User Preference Agents Information Broker Agents Buyer Agents Seller Agents Procurement Agents ……….

5. 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

6. ACORN (Agent-based Community Oriented Retrieval Network) Architecture Steve Marsh, Institute for Information Technology, NRC Virendra C. Bhavsar, Ali A. Ghorbani, UNB - Keyphrase-based Information Sharing between Agents Hui Yu – MCS Thesis (UNB) MATA’2000 Paper - Performance Evaluation using Multiple Autonomous Virtual Users HPCS’2000 paper ACORN (Agent-based Community Oriented Retrieval Network) Architecture Steve Marsh, Institute for Information Technology, NRC Virendra C. Bhavsar, Ali A. Ghorbani, UNB - Keyphrase-based Information Sharing between Agents Hui Yu – MCS Thesis (UNB) MATA’2000 Paper - Performance Evaluation using Multiple Autonomous Virtual Users HPCS’2000 paper

7. 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

8. Relation to Other Work Search Engines – Alta Vista, Excite, Yahoo, InfoSeek, Lycos, etc... – 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

9. 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

10. 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

11. Multi-Agent Systems B2B-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,

12. Multi-Agent Systems B2B-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

13. Multi-Agent Systems B2B-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

14. 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

15. 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

16. 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 satisfy many requirements in such an environment - Provide a very flexible and open architecture - Scalability analysis with multiprocessor servers

17. 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