The RatioLog Project: Rational Extensions of Logical Reasoning
  Higher-level cognition includes logical reasoning and the ability of question
answering with common sense. The RatioLog project addresses the problem of
rational reasoning in deep question answering by methods from automated
deduction and cognitive computing. In a first phase, we combine techniques from
information retrieval and machine learning to find appropriate answer
candidates from the huge amount of text in the German version of the free
encyclopedia "Wikipedia". In a second phase, an automated theorem prover tries
to verify the answer candidates on the basis of their logical representations.
In a third phase - because the knowledge may be incomplete and inconsistent -,
we consider extensions of logical reasoning to improve the results. In this
context, we work toward the application of techniques from human reasoning: We
employ defeasible reasoning to compare the answers w.r.t. specificity, deontic
logic, normative reasoning, and model construction. Moreover, we use integrated
case-based reasoning and machine learning techniques on the basis of the
semantic structure of the questions and answer candidates to learn giving the
right answers.
