A Markov Chain Representation of Human Reasoning and Scientific Thinking

Michael Gr. Voskoglou^1,

¹Mathematical Sciences, Graduate TEI of Western Greece, Patras, Greece

Cite this paper:
Michael Gr. Voskoglou. A Markov Chain Representation of Human Reasoning and Scientific Thinking. American Journal of Applied Mathematics and Statistics. 2020; 8(2):52-57. doi: 10.12691/ajams-8-2-3

Abstract

Reasoning is the most important human brain operation that leads to creative methodologies, algorithms and deductions giving way to sustainable research and development. Since the basis of reasoning in the Artificial Intelligence’s expert systems is human notions and concepts, the success of those systems depends upon the correspondence between human reasoning and their formalization. The paper at hands studies human reasoning in general and scientific thinking in particular with the help of the theory of finite Markov chains. Examples are also presented illustrating the applicability of the developed Markov chain models to real life situations.

Keywords:
Artificial Intelligence (AI) human reasoning scientific thinking probability theory Markov chain (MC) absorbing MC (AMC) ergodic MC (EMC)

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