Nonmonotonic reasoning is a discipline of computer science epistemology and cognition: It
models inferences where classical logic is inadequate in symbolic AI defines normative models
for reasoning with defeasible information in epistemology and models human reasoning under
information change in cognition. Its building blocks are defeasible rules formalised as
DeFinetti conditionals. In this thesis Christian Eichhorn examines qualitative and
semi-quantitative inference relations on top said conditionals using the conditional structure
of the knowledge base and Spohn's Ordinal Conditional Functions using established properties.
Converting network approaches from probabilistics he shows how to approach the relations with
regard to implementation.
