Buying properties and building houses and hotels on them, forcing the other players to pay ever more exorbitant rents… You guessed it: Monopoly, invented in the United States a century ago (see box below).
Since tokens move according to the chance outcome of the dice, one might think that Monopoly has little to offer from a mathematical standpoint. In fact, the game provides a textbook example of a Markov process, an important category of stochastic processes—systems that evolve randomly and can be studied using probability theory. Today, these processes are a major concern in applied mathematics, to the point that this field, which emerged in the early 20th century, is now among the most widely studied topics in research laboratories, across fields including telecommunications, epidemiology, and finance.
Markov processes and Markov chains
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A Markov process is a stochastic process in which knowing the situation at time n is enough to describe the probabilities of the various possible situations at time n + 1. Monopoly is one such process. If a token is on the Go space, it makes no difference whether the game has just begun or the player has just completed a full circuit: the probability that the dice will take the token to Rue Lecourbe is the same in both cases. Such a process is said to be memoryless: the past is of no help in predicting the future; only the present situation matters (see box below).