User feedback has an effect at two levels. One is at the population level, where the fitness of members of the population increases or decreases depending on the feedback. This is required for genetic learning. The other effect is on the profile, which is modified based on the features of the article the feedback is given for. The user can also program the agent by demonstrating examples of documents and providing feedback for those.
As will be clear in the description of the Information Filtering Module, the
document representation is generated while scoring the document and is not stored
thereafter. Therefore, when feedback for a retrieved document is provided, its
representation is no longer available for modifying the profile. This problem
is much more acute in programming by demonstration, where feedback is provided
for an article for which no representation has yet been created. The solution
adopted in this implementation is that the pointers of documents are stored
when feedback is provided, but the profiles are not immediately modified. The
list of items labeled ``ArtFeedback'' in table 
is the list of pointers to articles which received feedback in the last user
session. Next to the pointers is a positive or negative number indicating the
feedback for the article. The next time the Information Filtering module filters
articles, it re-creates the document representation for all articles and the
profile is then modified.