Generalizations of the M&M Game

TL;DR

This paper extends the classic MandM Game by introducing multiple coin tosses and varied probability distributions, employing generating functions, Monte Carlo simulations, and curve fitting to analyze the new game dynamics.

Contribution

It introduces several generalizations of the MandM Game, including multiple coin tosses and different probability models, and applies advanced analytical techniques to study them.

Findings

Derived new probability formulas for generalized game scenarios

Used simulations to validate theoretical results

Identified how game outcomes vary with different parameters

Abstract

The MandM Game involves two players who begin with I1 and I2 MandM's. During each round, each player tosses a fair coin: if the coin lands heads, that player eats one MandM, and if it lands tails, the player does not eat. If, at the end of a round, one player still has MandM's while the other has none, then the player with MandM's remaining is declared the winner. If both players eat their last MandM in the same round, the game is said to end in a tie. In [BHM+17], the authors studied the probability of a tie in the MandM Game and derived a simple closed-form expression in the special case where both players start with the same number of MandM's. We generalize the MandM Game in several directions, including allowing players to toss multiple coins per round and modifying the probability distributions of the coin flips. We use the technique of generating functions, Monte Carlo methods, and non-linear curve fitting to study the generalized MandM Game.