Modeling and Markov chains

Philippe Cohard

Abstract


Artificial intelligence and simulation are now topics with major interest for researchers and practitioners. Markov chain is a powerful approach of simulation that could be used in multiple area. For example, in management this approach can give numerous opportunities to better understand phenomena. Thus we ask the question: “How can Markov chains be useful to simulate processes? “. This paper is our answer. With Markov chains we show the possibilities to better understand management project. We also propose two programs which explain how to implement these simulations based on Markov chains. The results show that Markov chains approach of simulation can be useful for teaching and explaining processes. Simulation gives data to analyse what can be compared with empirical data or tested for coherence. Simulation with Markov chain can be interpreted and give insights on real causes of complex phenomena.


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