Optimal strategies in the all-heads coin game
Peter Pfaffelhuber

TL;DR
This paper analyzes a sequential coin-flipping game, determining optimal strategies and winning probabilities based on the number of coins and bias, with explicit formulas and perturbation analysis near p=1/2.
Contribution
It provides a detailed analysis of optimal strategies and explicit formulas for winning probabilities in the all-heads coin game, including perturbation results near p=1/2.
Findings
For p=1/2, all strategies have a 50% winning probability.
For p>1/2, the 'set aside one head' strategy is optimal.
Near p=1/2, the winning probability exhibits a linear perturbation with a specific limit.
Abstract
We study a sequential coin-flipping game in which a player starts with~ coins, each landing heads independently with probability~. In each round the player flips all remaining coins and must set aside at least one coin showing heads; if no coin shows heads, the player loses. The player wins if and when all coins have been set aside. This is a stochastic shortest-path Markov decision process whose Bellman equation involves a nonlinear suffix-maximum operator. We analyse two natural strategies -- \One{} (set aside exactly one head) and \All{} (set aside every head) -- and determine the optimal winning probability~ as a function of~ and~. For every strategy achieves . For the strategy~\One{} is optimal and is strictly increasing; as a consequence the limit admits an explicit…
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