Non-Monotonic Reasoning and Story Comprehension
  This paper develops a Reasoning about Actions and Change framework integrated
with Default Reasoning, suitable as a Knowledge Representation and Reasoning
framework for Story Comprehension. The proposed framework, which is guided
strongly by existing knowhow from the Psychology of Reading and Comprehension,
is based on the theory of argumentation from AI. It uses argumentation to
capture appropriate solutions to the frame, ramification and qualification
problems and generalizations of these problems required for text comprehension.
In this first part of the study the work concentrates on the central problem of
integration (or elaboration) of the explicit information from the narrative in
the text with the implicit (in the readers mind) common sense world knowledge
pertaining to the topic(s) of the story given in the text. We also report on
our empirical efforts to gather background common sense world knowledge used by
humans when reading a story and to evaluate, through a prototype system, the
ability of our approach to capture both the majority and the variability of
understanding of a story by the human readers in the experiments.
