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.
- Properties of Nonmonotonic Reasoning
- Reasoning with Sets of c-Representations
- Network Approaches to Ordinal Conditional Functions
- Formal Inferences and Commonsense Reasoning: Connections to Psychology and Cognition
- Academics and students of computer science, cognitive science and theoretical philosophy
- Information scientists and experimental psychologists
Christian Eichhorn received his doctorate from the Computer Science Department at the Technical University, Dortmund. His research was supported by the interdisciplinary Priority Programme SPP1516 „New Frameworks of Rationality” of the Deutsche Forschungsgemeinschaft.