Thinking Between the Lines targets a challenge at the heart of the artificial intelligence enterprise: the design of programs that can read and reason on the basis of written causal descriptions such as those that appear in encyclopedias, user manuals, and related sources. This capability of "thinking between the lines"—codified in terms of a task called "causal reconstruction"—bears directly on the larger question of how computers can usefully exploit the vast repertory of human knowledge concerning causal phenomena.
