Argument-Based Logic Programming for Analogical Reasoning

Analogical reasoning can be understood as a kind of resemblance of one thing to another, thus assigning properties from one context to another. The key idea is to use similarity information to support an inference which cannot be deductively inferred. In this paper, we present a formal and intuitive framework of this phenomena using an argument-based logic-programming-like language. A proof theory of our system is stated in the dialectical style, where a proof takes the form of dialogue between a proponent and an opponent of an argument. We also discuss how the proposed framework can be fine tuned for optimistic analogical reasoning and pessimistic analogical reasoning. Finally, we discuss a design sketch of our proposed analogical reasoner called Analogist.