Multi-Agent Systems for e-Commerce Virendra C. Bhavsar Professor and

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) 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) MATA’2000 Paper- Performance Evaluation using Multiple Autonomous Virtual Users HPCS’2000 paper

7. ACORNAgent-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 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,

12. 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

13. Multi-Agent SystemsB2B-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