Developing an Optimal Strategy for a Maximization Dice Game

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Acknowledgments

The authors are very grateful to the two anonymous reviewers for their constructive comments, which have greatly improved the paper. In particular, one of the reviewers contributes the idea and results of the simplified decision tree method presented in this article. We would like to thank the reviewers for their heroic efforts.

Summary

We develop an optimal strategy for a maximization dice game which starts with throwing five dice simultaneously and declaring at least one of them to be frozen. The process is repeated and the player with the largest total on all frozen dice wins the game.

Additional information

Notes on contributors

Kevin L.T. Chan

Kevin L.T. Chan ([email protected]) graduated with a B.S.B.A. degree (double-major in finance and accounting) at the Questrom School of Business, Boston University. He is currently pursuing a master’s degree in business analytics and risk management at Johns Hopkins University. Kevin is a serious table tennis player and has served as the captain of the Boston University Team.

Wai-Sum Chan

Wai-Sum Chan ([email protected], MR ID: 327913) is a professor of finance at the Chinese University of Hong Kong, PR China. Wai-Sum received his Ph.D. in Statistics from Temple University, Philadelphia. In his free time, he enjoys playing ancient Chinese dice games with his son, who is the first author of this article.