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Related papers: Rigorous computer analysis of the Chow-Robbins gam…

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The payoff in the Chow-Robbins coin-tossing game is the proportion of heads when you stop. Knowing when to stop to maximize expectation was addressed by Chow and Robbins(1965), who proved there exist integers ${k_n}$ such that it is optimal…

Probability · Mathematics 2023-06-07 John H. Elton

The Chow-Robbins game is a classical still partly unsolved stopping problem introduced by Chow and Robbins in 1965. You repeatedly toss a fair coin. After each toss, you decide if you take the fraction of heads up to now as a payoff,…

Probability · Mathematics 2021-10-07 Sören Christensen , Simon Fischer

In a recent article in American Scientist, Theodore Hill described a coin-tossing game whose pay-off is the number of heads over the total number of throws. Suppose that at a given point during the game you have 5 heads and 3 tails, should…

Probability · Mathematics 2010-09-13 Luis A. Medina , Doron Zeilberger

We study a game in which one keeps flipping a coin until a given finite string of heads and tails occurs. We find the expected number of coin flips to end the game when the ending string consists of at most four maximal runs of heads or…

Combinatorics · Mathematics 2025-01-31 Jia Huang

We study a sequential coin-flipping game in which a player starts with~$n$ coins, each landing heads independently with probability~$p$. In each round the player flips all remaining coins and must set aside at least one coin showing heads;…

Probability · Mathematics 2026-04-28 Peter Pfaffelhuber

An algorithm based on backward induction is devised in order to compute the optimal sequence of games to be played in Parrondo games. The algorithm can be used to find the optimal sequence for any finite number of turns or in the steady…

Physics and Society · Physics 2014-09-24 L. Dinis

You play the following game: you start out with $n$ coins that all have probability $p$ to land heads. You toss all of them and you then need to set aside at least one of them, which will not be tossed again. Now you repeat the process with…

Combinatorics · Mathematics 2024-06-25 Wouter van Doorn

We study the problem of learning a most biased coin among a set of coins by tossing the coins adaptively. The goal is to minimize the number of tosses until we identify a coin i* whose posterior probability of being most biased is at least…

Data Structures and Algorithms · Computer Science 2013-09-10 Karthekeyan Chandrasekaran , Richard Karp

It is well-known that for infinitely repeated games, there are computable strategies that have best responses, but no computable best responses. These results were originally proved for either specific games (e.g., Prisoner's dilemma), or…

Computer Science and Game Theory · Computer Science 2020-06-11 Jakub Dargaj , Jakob Grue Simonsen

Understanding the properties of games played under computational constraints remains challenging. For example, how do we expect rational (but computationally bounded) players to play games with a prohibitively large number of states, such…

Computer Science and Game Theory · Computer Science 2021-05-20 Thomas Orton

What is the average number of tosses needed before a particular sequence of heads and tails turns up? We solve the problem didactically, starting with doubles, finding that a tail, followed by a head, turns up on the average after only four…

Probability · Mathematics 2019-10-08 Porter W. Johnson , David Atkinson

We introduce and analyze a natural game formulated as follows. In this one-person game, the player is given a random permutation $A=(a_1,\dots, a_n)$ of a multiset $M$ of $n$ reals that sum up to $0$, where each of the $n!$ permutation…

Discrete Mathematics · Computer Science 2024-11-21 Adrian Dumitrescu , Arsenii Sagdeev

We develop an approach to solve Barberis (2012)'s casino gambling model in which a gambler whose preferences are specified by the cumulative prospect theory (CPT) must decide when to stop gambling by a prescribed deadline. We assume that…

Mathematical Finance · Quantitative Finance 2021-02-08 Sang Hu , Jan Obloj , Xun Yu Zhou

Many learning algorithms are known to converge to an equilibrium for specific classes of games if the same learning algorithm is adopted by all agents. However, when the agents are self-interested, a natural question is whether agents have…

Computer Science and Game Theory · Computer Science 2024-02-15 Shivam Bajaj , Pranoy Das , Yevgeniy Vorobeychik , Vijay Gupta

Escalation is a typical feature of infinite games. Therefore tools conceived for studying infinite mathematical structures, namely those deriving from coinduction are essential. Here we use coinduction, or backward coinduction (to show its…

Computer Science and Game Theory · Computer Science 2010-04-30 Pierre Lescanne , Perrinel Matthieu

Escalation is a typical feature of infinite games. Therefore tools conceived for studying infinite mathematical structures, namely those deriving from coinduction are essential. Here we use coinduction, or backward coinduction (to show its…

Computer Science and Game Theory · Computer Science 2011-12-16 Pierre Lescanne , Perrinel Matthieu

We study a robust optimal stopping problem with respect to a set $\cP$ of mutually singular probabilities. This can be interpreted as a zero-sum controller-stopper game in which the stopper is trying to maximize its pay-off while an adverse…

Probability · Mathematics 2016-04-12 Erhan Bayraktar , Song Yao

The takeoff point for this paper is the voluminous body of literature addressing recursive betting games with expected logarithmic growth of wealth being the performance criterion. Whereas almost all existing papers involve use of linear…

Optimization and Control · Mathematics 2024-01-17 Anton V. Proskurnikov , B. Ross Barmish

A Dynkin game is a zero-sum, stochastic stopping game between two players where either player can stop the game at any time for an observable payoff. Typically the payoff process of the max-player is assumed to be smaller than the payoff…

Probability · Mathematics 2020-08-18 Ivan Guo

We study Stackelberg equilibria in finitely repeated games, where the leader commits to a strategy that picks actions in each round and can be adaptive to the history of play (i.e. they commit to an algorithm). In particular, we study…

Computer Science and Game Theory · Computer Science 2024-03-08 Natalie Collina , Eshwar Ram Arunachaleswaran , Michael Kearns
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