Using I-net Agents
Creating Individual Views From
Unstructured Content
Bart Meltzer and Steve Telleen
iorg.com
The world of human communication and information has long been too
voluminous
and complex for any one individual to monitor and track. To cope with
the
information overload, we have learned to create organizations that
divide
and delegate responsibilities for the creation, monitoring, management,
organization
and presentation of information. The bureaucratic organizational
structures
of most modern corporations and governments are the instantiation of
how
these information responsibilities have been delegated so the
information
flows efficiently into the creation of specific goods or services. We
use
the term bureaucratic to describe the rigid structure and processes
that
allow the delegated information to be efficiently and consistently
reassembled
to meet the corporate goals.
Today, these traditional ways of dealing with
information
are again under stress. Organizations have grown too large, the
environment
too complex and the information too ubiquitous for the carefully
pre-structured
relationships of the past to keep pace. As executives and managers we
are
told to decentralize, distribute and empower all aspects of our
business.
While the benefits in flexibility and market responsiveness often are
obvious,
the process also amplifies the information explosion. To make matters
worse,
the organizational structures eliminated to create the business
benefits
are the same structures we relied on in the past to organize and share
information.
So how do we deal with what looks like information chaos? Fortunately,
two
complimentary technologies have emerged that allow us to coordinate,
communicate
and even organize information, without rigid, one-size-fits-all
structures. The first is the Internet/Web technologies, that we will
refer to as I-net technology, and the second is the evolution of
software agents.
Together, these technologies are the new-age
building
blocks for robust information architectures, designed to help
information
consumers find what they are looking for in the way that they want to
find
it. The web and software agents make it possible to build
sophisticated,
well performing information brokers designed to deliver content, from
multiple
sources, to each individual, in the individual's specific context and
under
the individual's own control. This is more than a search engine. This
is
the ability to provide meaningful information to each individual based
on
her needs, and a way to improve the information supplier/consumer
relationship by providing the information consumer with more precise
control over the interaction.
In our context, an agent is, simply put, one who
takes
action at the instigation of another. The concept of agents, in our
sense,
is not new or restricted to software. According to the Oxford
English
Dictionary, this meaning of the term in the English language dates
at
least as far back a 1593. In one of the author's previous writings, the
concept
of an information broker is clearly an agent function. What is new is
the
ability to create extremely powerful, flexible and individualized
software
agents because of the I-net infrastructure. These software agents can
be
highly effective tools for individualizing the organization and
management
of distributed information.
The world of software agents remains a poorly
understood
and extremely urgent area of I-net activity. It is urgent because a
plethora
of software products are on the market today that are acting as
software
agents, and yet there seems to be little understanding by the software
vendors
or consumers of what an I-net software agent is, or could be. The much
hyped
channel technology (often mislabled as Push) is but one example of the
confusion that results by not recognizing that these software products
are agents that
can be understood within a larger conceptual framework. The remainder
of
this article will present some key aspects of the software agent
framework.
From the agent employer's perspective, the agent
is
a service whose location should be as transparent as the rest of the
content
on the I-net. Whether a specific agent's logic resides on the
employer's
local system or is a service on a remote system becomes an
architectural
decision based on system capabilities and load balancing
considerations,
rather than the agent service itself. Some basic collection services
are
best aggregated at logical concentration points to ease network
traffic.
For example, a primitive form of agent technology is the spider-based
index
of an intranet. There is no technical reason why each individual could
not
have a spider-based agent on their local system to search the intranet
either
generally or specifically. However, in practice, the network
infrastructure
would quickly become overwhelmed. It is architecturally more efficient
to
have the intranet searched regularly by a single spider-based agent
that
catalogs the content for use by other agents (say a traditional search
engine)
employed by each individual. Again, the logic for a general purpose
search
engine may be more appropriately placed as a shared service on a remote
system,
while more specialized and sophisticated agents may access the catalog
from
a remote system but themselves reside on a local system. Many web-based
merchants already provide their patrons with site-specific agent
services that parse the content on their site to each individual's
interests, or track changes in specific content identified by the
individual and display these changes the next time the individual
visits the site or send an email notification to the individual when
the change occurs.
As we begin to develop more sophisticated
information
agents, a general classification of different types of agents becomes
useful.
At the highest level, there are two basic functions that information
agents
perform, sensory functions and action functions. Sensory agents
discover,
collect and organize information from the system at large. The
spider-based
agents and search engines discussed above are examples of sensory
agents.
Action agents cause changes in other parts of the system at large.
Computer
viruses are an example of an action agent. This distinction between
sensory
and action information appears to be based in nature. Our own nervous
systems
are divided into two separate systems, one for collection of
information,
the other for acting on information. In biology, the terms affective
and
effective are the names used to differentiate these two nervous
systems.
Sensory agents can be further distinguished as
scanning
agents, screening agents or tracking agents. Scanning agents are the
most
general in that they collect and organize information that is not
focused
on a specific goal. Spiders and other general cataloging services are
examples
of scanning agents. General "browsing" of the web is a scanning
activity.
Screening agents, essentially, perform pattern matching services. The
agent
screens the information and only delivers information from sources that
match
the requested pattern. Search engines are one example of a screening
agent. Dynamic pages built from patron provided profiles are another
example of a
screening agent. Tracking agents are even more specific. The employer
of
the agent identifies a specific target to be tracked and specifies
certain changes or states in which she is interested. The agent then
monitors the target on a regular basis and reports back only when the
specified changes occur. Agents that allow an information consumer to
target a specific page, or content on a page, and then notify the
consumer when a change occurs are
tracking agents. Agents that track each visitor's activities and report
back
only when encountering specific access patterns (for either security or
marketing
reasons) are another example of tracking agents.
We have identified two types of action agents:
those
that modify content and those that activate or deactivate processes.
Action
agents may operate by knowing how to activate (and repurpose) existing
processes,
or they may require the target to have specific logic installed that
they
can manipulate. A computer virus is an example of the former, while
cookies,
software-update agents and system management agents generally are
examples
of the latter. Some of the uses of cookies may be viewed as the former
case
when sites stretch the cookies original intent and collect other
information
about the visitor without the visitor's consent. Publishing agents can
be
either. Problems arise when desirable action agents require logic in
the
target that is not part of a community-owned standard. If one views
channel
technologies as action agents, the current vendor battles can easlily
be
understood as a lack of community-owned standards for the logic in the
targets.
The term "Push" recently has been a hot marketing
buzz-word.
However, even a cursory analysis of products billed as "push" quickly
indicate
that the term is widely misused. Since push and pull are
characteristics
of agents, we propose the following three definitions to help clarify
the concepts.
- Push is information that is:
- Not requested
- Delivered at the convenience of the
publisher or agent
- Pull is information that is:
- Requested
- Delivered at the convenience of the
information consumer
- Subscription is information that is:
- Requested
- Delivered at the convenience of the
publisher or agent.
Using these definitions we can begin to classify our requirements and
intentions for specific actions and agents and use the results to
create more effective communication architectures. We also can use
these definitions to untangle the products currently lumped together in
the push category and separate them
into those that are true push, those that are automated pull-agents and
those
that are subscription agents. By more accurately defining our needs and
our
tools we improve our effectiveness. As a general rule, true push agents
should
be highly controlled and used sparingly in organizations to minimize
information
overload. Automated pull and subscription agents, that allow individual
control
by each information consumer, should be encouraged to reduce
information
overload.
It is easy to see that before long agent
development
will need to address how agents interact with each other rather than
just
with people. In the past we would have approached this problem by
attempting
to standardize processes across all agents. Our experience with I-nets
suggests
that a more productive approach may be standardize content (like we did
with
HTML/HTTP) and use specialized agents to provide inter-agent
interfaces.
In this model, agents begin to look like information versions of
hormones
and enzymes in biological systems rather than the highly structured
parts
of earlier machine models. One even begins to wonder if the "one gene,
one
enzyme" rule of biological systems might be translated as "one agent,
one
function" for efficient I-net development.
As we move to these new models, our goal-directed
intranets
and extranets will continue to require well architected infrastructures
to
maintain flexibility and create efficiencies. This is true today
because
many tools are not based on community-owned standards, and most
approaches
are implicitly based on creating homogeneity rather than supporting
diversity.
As our infrastructures begin to incorporate community-owned standards
and
a preference for diversity, intranet and extranet architectures will
continue
to be important as evolving, competitive differentiators.
Summary and Conclusions
Agents and I-net standards are the building blocks
that
make individual customization of information possible in the
unstructured
environment of I-nets. Agents will begin to specialize and become much
more
than today's general purpose search engines and "push" technologies.
Successful
application vendors will rethink their applications, replacing
structured
forms with increasingly specialized agents to support both sensory and
action
functions within specific, user-defined contexts. Well developed
architectures,
based on community-owned standards, and robust tools that support the
standards are critical to a successful implementation of agent
technology. The new agents
will move us from the "one-size-fits-all" approach of today's
applications into a world that allows individual users to find, use and
share what they want, the way that they want it.
Copyright 1997, Bart Meltzer
and
Steve Telleen
bart@cngroup.com
- stevet@iorg.com
Last updated: June 24, 1997
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