A Fuzzy Model for Analogical Problem Solving
Artificial Intelligence
2012-05-01 v1
Abstract
In this paper we develop a fuzzy model for the description of the process of Analogical Reasoning by representing its main steps as fuzzy subsets of a set of linguistic labels characterizing the individuals' performance in each step and we use the Shannon- Wiener diversity index as a measure of the individuals' abilities in analogical problem solving. This model is compared with a stochastic model presented in author's earlier papers by introducing a finite Markov chain on the steps of the process of Analogical Reasoning. A classroom experiment is also presented to illustrate the use of our results in practice.
Keywords
Cite
@article{arxiv.1204.6415,
title = {A Fuzzy Model for Analogical Problem Solving},
author = {Michael Gr. Voskoglou},
journal= {arXiv preprint arXiv:1204.6415},
year = {2012}
}
Comments
10 pages, 1 Table