Probability and Fuzzy Logic in Analogical Reasoning

Abstract

Analogical Reasoning (AR) is a method of processing information that compares the similarities between new and past understood concepts, then using these similarities to gain understanding of the new concept. In this work we develop two mathematical models for the description of the process of AR: A stochastic model by introducing a finite ergodic Markov chain on the steps of the AR process and a fuzzy model by representing the main steps of the AR process as fuzzy subsets of a set of linguistic labels characterizing the individuals’ performance in each of these steps. The two models are compared to each other by listing their advantages and disadvantages. Classroom experiments are also performed to illustrate their use in practice