Pleiades Project Home Page
Tom Mitchell and Katia Sycara, CMU School of
Our objective is to create and demonstrate
In order to explore these issues, we have developed a collection of four
interacting software agents:
- machine learning methods that allow personal software agents to
automatically customize to the needs of their users, and
- methods for automated negotiation among these agents, in order to improve
their effectiveness, robustness, scalability and maintainability.
system diagram illustrates the interactions among these agents.
- a Calendar Apprentice (CAP) which learns users' scheduling
preferences (see our
most recent paper, or
click here for access to some of the data
used in our experiments),
- a Mosaic-based netnews reader (NewsWeeder) that learns users'
reading interests ( try
- a Mosaic-based tour guide (WebWatcher) that helps you search for
information, and learns from experience. See the project home page.
- a Visitorhost which helps
schedule visitors for technical briefings, and
- a Personnel Information mediator which provides information about specific individuals and their jobs.
See our list of
Research support: Arpa, Digital, Siemens
Last Updated: 7/7/94