Apt Decision Agent
In complex domain spaces, people give minimal/incomplete/incorrect descriptions
of what they want. Why?
- They don't know what they really want
- They forgot some crucial piece of information or level of detail
- They lack information that an agent could give them
Computer programs attempt to solve this problem, but they often fail. Why?
- They require decisions before the user has the information to make them
- They often don't incorporate knowledge about the domain in a way that is
accessible to the user.
- They don't learn anything about the users' choices or preferences
The Apt Decision Agent:
- Helps the user make decisions in a complex domain space (real estate)
- Helps the user learn about the domain and recall details about choices
- Learns from the user's behavior by observing interactions with the system
- Provides the user with a familiar style of interface which has 'extra'
How it works:
- The user enters minimal information to start, enough to generate a list
of potential apartments.
- While the agent watches, the user chooses desirable or undesirable attribute
values from the apartments shown.
- The agent, using its knowledge of the real estate domain, learns the user's
preferences, and offers suggestions based on those preferences. Preferences
are stored in a profile.
- Through successive iterations, the agent adjusts the user's profile with
increasing certainty. The profile can be saved and 'handed off' to negotiation
or shopping agents
Download paper (PDF)
An Apt Decision presentation from summer 2000.