BISC: BISC Seminar: March 1, 2001

From: Masoud Nikravesh (nikravesh@eecs.berkeley.edu)
Date: Fri Feb 23 2001 - 13:49:30 MET

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    *********************************************************************
    Berkeley Initiative in Soft Computing (BISC)
    *********************************************************************

    Upcoming Seminars:

    Mark your Calendar for BISC Special Seminar Series (March 8, 2001)
    Charles L. Ortiz, Jr.: Interpreting information requests in context
    4:00pm-5:00pm
    **5:00pm-5:45 pm; Discussion to follow seminar**
    =================================================

    Intelligent Agents, Teamwork, and Personalization

    John Yen
    Department of Computer Science
    Texas A&M University

    March 1, 2001
    380 Soda Hall
    4:00-5:00 pm

    Information and knowledge delivered by the internet and wireless devices are
    reshaping every aspects of human life and business enterprises. At a speed we
    could have never imaged before, information and knowledge is constantly being
    created, delivered, and processed globally. There are at least two challenges
    ahead of us, however. First, the capabilities of knowledge processing will
    increase rapidly both in breadth and in depth due to the increasing emphasis on
    ``business intelligence''. For instance, the next-generation workflow
    automation and coordination model needs to adapt itself to the changing business
    environment, to support information exchanges based on anticipating information
    needs of other coworkers within and between functional areas. Second, knowledge
    used for machine processing needs to be easily understood by users, be able to
    improve itself from experience, and be protected and traded under suitable
    policy. In brief, knowledge will be embedded in devices of all kinds, be used
    in everything we do, and be viewed as a commodity.

    In this talk, I will describe two research activities related to these two
    challenges. Our research on agent-based teamwork modeling is the first to focus
    on proactive delivery of information based on predicting information needs of
    team members. The goal of this research is to simulate the shared mental model
    of a team by capturing their knowledge about the team's processes, by inferring
    their belief about the states of teammates, and by taking actions that meet the
    needs of self as well as others in the team. To accomplish these, we have
    developed a novel language for representing teamwork knowledge (called MALLET),
    a team-based agent architecture called CAST (Collaborative Agents for Simulating
    Teamwork) that uses knowledge compiled from MALLET, and an algorithm (called
    IARG) for generating proactive information exchanges between agents. The CAST
    teamwork agent model is being applied to AWACS crew training (under an AFOSR
    MURI grant) and to simulating battalion TOC (tactical operation center) for
    training brigade battle staff (under an Army Digitization Initiative). Even
    though CAST was motivated by military decision support and training needs, it
    provides a unique foundation for developing the next-generation workflow models
    to support E-business in the 21st century.

    The second thrust of my current research is on learning of user interest
    dynamics. The Web has enabled a wide range of personalized services. However,
    learning user interests reliably remained a hard problem because some of the
    interests come and go in days or weeks, while others stay for months or even
    longer. To adapt to changes to both short term and long term user interests, we
    developed a novel three-descriptor model for user profiling. The proposed model
    maintains a long-term interest descriptor to capture the user's general
    interests and a short-term interest descriptor to keep track of the user's more
    recent, faster-changing interests. An algorithm based on the three-descriptor
    representation is developed to acquire high accuracy of recognition for
    long-term interests, and to adapt quickly to changing interests in the
    short-term. Empirical studies confirm the effectiveness of the scheme to
    accurately model a user's interests and to adapt appropriately to various levels
    of changes in the user's interests.

    Biography

    Dr. John Yen is currently a Professor of Computer Science at Texas A&M
    University and the Director of Center for Fuzzy Logic, Robotics, and Intelligent
    Systems. He received his Ph.D. in Computer Science from University of
    California at Berkeley in 1986. From 1986 to 1989, he was a Research Scientist
    at Information Sciences Institute (ISI), University of Southern California.
    Since 1989, he has been on the faculty of Computer Science Department at Texas
    A&M University. His research has been dedicated to the creation and the
    processing of knowledge for machine intelligence, with an earlier emphasis on
    uncertainty and a later concentration on intelligent agents. He is currently a
    PI/Co-PI of two multi-million dollar research projects funded by the DOD. He
    has published more than 100 technical papers in journals, conference
    proceedings, and edited volumes. He is a member of Editorial Board of several
    international journals. He received an NSF Young Investigator Award in 1988, and
    he is a Fellow of IEEE.

    -- 
    Dr. Masoud NikRavesh
    Research Engineer - BT Senior Research Fellow
    Chair: BISC Special Interest Group on Fuzzy Logic and Internet
    Visiting Scientist: Lawrence Berkeley National Lab, 
    (Imaging and Collaborative Computing Group) 
    

    Berkeley initiative in Soft Computing (BISC) Computer Science Division- Department of EECS University of California, Berkeley, CA 94720 Phone: (510) 643-4522 - Fax: (510) 642-5775 Email: nikravesh@cs.berkeley.edu URL: http://www.cs.berkeley.edu/~nikraves/ URL: http://www-bisc.cs.berkeley.edu/ (BISC Homepage) URL: http://vision.lbl.gov/ URL: http://www.zadeh.cs.berkeley.edu/ (Sponsor's Homepage) -------------------------------------------------------------------- If you ever want to remove yourself from this mailing list, you can send mail to <Majordomo@EECS.Berkeley.EDU> with the following command in the body of your email message: unsubscribe bisc-group or from another account, unsubscribe bisc-group <your_email_adress>

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