ABSTRACT:

In this invited talk we present research, development and applications of 
cognitive agents that integrate three complementary capabilities: 
(1) they are able to learn, directly from their users, the subject matter 
expertise which currently takes years to establish, is lost when experts 
separate from service, and is costly to replace; 
(2) they can tutor new users in expert problem solving; and 
(3) they can assist their users in solving complex problem in uncertain 
and dynamic environments. 
While the applications of such agents are practically unlimited, we will 
illustrate them in the domain of intelligence analysis where they help the 
intelligence analysts in discovering and evaluating evidence and hypotheses 
by developing Wigmorean probabilistic inference networks that link evidence 
to hypotheses in argumentation structures that establish the relevance, 
believability and inferential force of evidence.