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What is Finite Markov Chain (FMC)

Handbook of Research on Applied AI for International Business and Marketing Applications
A MC with a finite number of states.
Published in Chapter:
Use of Finite Markov Chains in Business Problems Involving Decision Making and Case-Based Reasoning
Michael Voskoglou (Graduate Technological Educational Institute of Western Greece, Greece)
DOI: 10.4018/978-1-7998-5077-9.ch016
Artificial intelligence (AI) is the branch of computer science focusing on the creation of intelligent machines that mimic human reasoning and behaviour. Probability theory is among the mathematical tools used in AI applications to deal with situations of uncertainty caused by randomness. In particular, the Markov chain (MC) theory is a smart combination of probability and linear algebra that offers ideal conditions for modelling such situations. International business is about the trade of goods, services, technology, capital, and knowledge at a global level, while decision making (DM) and case-based reasoning (CBR) are among the processes that are frequently used in this field. In this chapter, an absorbing and an ergodic MC model are developed on the steps of DM and CBR respectively for representing mathematically those two processes, thus providing valuable information about their evolution. The examples presented are connected to international business applications.
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