@incollection{cybenko:push,
    author = {George Cybenko and Brian Brewington},
    title = {The Foundations of Information Push and Pull},
    booktitle = {Mathematics of Information},
    editor = {D. O'Leary},
    year = {1998},
    publisher = {Springer-Verlag},
    copyright = {Springer-Verlag},
    group = {agents},
    url = {http://agent.cs.dartmouth.edu/papers/cybenko:push.ps.gz},
    keyword = {information retrieval},
    abstract = {Information push and information pull have recently emerged as
useful concepts to describe the operation of distributed information
resources. Information push, in particular, is becoming closely associated
with intelligent agent functionality. \par Loosely speaking, if a user
requests and receives a very specific piece of information, this is
information pull. If information is sent in anticipation of the user's need,
or the agent's response includes information not directly solicited, then the
situation is characterized as information push. Intuitively, junk mail
(electronic or paper), television newscasts and wirefeeds are examples of
information push. New web services such as Pointcast and Informant are
examples of more selective push technologies. Web browsing, library searches,
and telephone white pages are traditional examples of information pull. \par
Clearly, these categorizations can be ambiguous and are easily lost in
semantics. The main goal of this paper is to formalize these concepts and
describe a mathematical framework around which further work can be more
precise. Specifically, we develop a stochastic framework based on Markov
models to describe an ambient environment and an agent system. Depending on
the relationships between the environment, the agent and the user's
performance criterion, a continuum of possible information push and pull
scenarios can be described. Some basic analytic results concerning the
operation of a push/pull information system are derived.}
}