Supports conditional processing
Many agents use rule based pattern matching logic to make decisions
in the face of changing context.
As agents become more sophisticated, these rules will increasingly be
able to be stated at a higher level, even natural language.
Learning
Some of the newer internet search engines boast intelligent agents,
which can learn from previous requests the user has made.
Reactivity
Agents perceive their environment which may be the physical world, a
user via graphical user interface, a collection of other agents, the
internet, or perhaps all of these combined and respond in a timely
fashion to changes that occur in it.
Proactive ness
Agents do not simply act in response to their environment. They are
able to exhibit goal defected behavior by taking initiative.
Temporal continuity
The agent should be a continuously running process, not a one shot
deal that terminates after completing a series of commands.
Personality
For an agent to be effectively, it must be believable and be able to
interact with human users.
Mobility
An agent that can transport it across different system architectures and
platforms is far superior to those that cannot.
Why intelligent Agents.
Information access and navigation are today’s major applications of
intelligent agents, but there are several other reasons why this
technology is expected to grow rapidly.
Examples _ Intelligent agents can improve computer network security,
support electronic commerce, empower employees, and increase
productivity and quality
Following are the reasons.
1) Decision Support 4) Search and retrieval
2) Repetitive office activity 5) Domain experts
3) Mundane personal activity
Decision support
There is a need for increased support for tasks performed by
knowledge workers, especially in the decision machine area.
Timely and knowledgeable decisions businesses in the marketplace.
Repetitive office activity
There is a pressing need to automate tasks performed by
administrative and clerical personnel in functions such as sales or
customer support to reduce labor costs and increase office productivity.
Mundane personal activity
In a fast paced society, time strapped people need new ways to
minimize the time spent on routine personal tasks such as booking
airline tickets so that the voice activated interface Aetna that reduces
the burden on the user of having to explicitly command the computer.
Another is that of a personal assistant, whom learns our work patterns
and replicates the on typical but mundane tasks such as appointments,
meal reservations, and e mail processing.
Search and retrieval
It is not possible to directly manipulate a distributed database system in
an electronic commerce setting with millions of data objects.
These agents perform the tedious, time consuming and repetitive tasks
of searching databases, retrieving and filtering information and
delivering it back to the user.
Domain experts
It is advisable to model costly expertise and make it widely available.
Examples of expert software agents could be models of real world
agents such as translators, lawyers, diplomats, union negotiators,
stockbrokers, and even clergy.
Many agents use rule based pattern matching logic to make decisions
in the face of changing context.
As agents become more sophisticated, these rules will increasingly be
able to be stated at a higher level, even natural language.
Learning
Some of the newer internet search engines boast intelligent agents,
which can learn from previous requests the user has made.
Reactivity
Agents perceive their environment which may be the physical world, a
user via graphical user interface, a collection of other agents, the
internet, or perhaps all of these combined and respond in a timely
fashion to changes that occur in it.
Proactive ness
Agents do not simply act in response to their environment. They are
able to exhibit goal defected behavior by taking initiative.
Temporal continuity
The agent should be a continuously running process, not a one shot
deal that terminates after completing a series of commands.
Personality
For an agent to be effectively, it must be believable and be able to
interact with human users.
Mobility
An agent that can transport it across different system architectures and
platforms is far superior to those that cannot.
Why intelligent Agents.
Information access and navigation are today’s major applications of
intelligent agents, but there are several other reasons why this
technology is expected to grow rapidly.
Examples _ Intelligent agents can improve computer network security,
support electronic commerce, empower employees, and increase
productivity and quality
Following are the reasons.
1) Decision Support 4) Search and retrieval
2) Repetitive office activity 5) Domain experts
3) Mundane personal activity
Decision support
There is a need for increased support for tasks performed by
knowledge workers, especially in the decision machine area.
Timely and knowledgeable decisions businesses in the marketplace.
Repetitive office activity
There is a pressing need to automate tasks performed by
administrative and clerical personnel in functions such as sales or
customer support to reduce labor costs and increase office productivity.
Mundane personal activity
In a fast paced society, time strapped people need new ways to
minimize the time spent on routine personal tasks such as booking
airline tickets so that the voice activated interface Aetna that reduces
the burden on the user of having to explicitly command the computer.
Another is that of a personal assistant, whom learns our work patterns
and replicates the on typical but mundane tasks such as appointments,
meal reservations, and e mail processing.
Search and retrieval
It is not possible to directly manipulate a distributed database system in
an electronic commerce setting with millions of data objects.
These agents perform the tedious, time consuming and repetitive tasks
of searching databases, retrieving and filtering information and
delivering it back to the user.
Domain experts
It is advisable to model costly expertise and make it widely available.
Examples of expert software agents could be models of real world
agents such as translators, lawyers, diplomats, union negotiators,
stockbrokers, and even clergy.
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