A Computational Proof of the Highest-Scoring Boggle Board
Data Structures and Algorithms
2025-07-04 v1
Abstract
Finding all the words on a Boggle board is a classic computer programming problem. With a fast Boggle solver, local optimization techniques such as hillclimbing and simulated annealing can be used to find particularly high-scoring boards. The sheer number of possible Boggle boards has historically prevented an exhaustive search for the global optimum board. We apply Branch and Bound and a decision diagram-like data structure to perform the first such search. We find that the highest-scoring boards found via hillclimbing are, in fact, the global optima.
Keywords
Cite
@article{arxiv.2507.02117,
title = {A Computational Proof of the Highest-Scoring Boggle Board},
author = {Dan Vanderkam},
journal= {arXiv preprint arXiv:2507.02117},
year = {2025}
}
Comments
14 pages, 2 figures, code available at https://github.com/danvk/hybrid-boggle/