Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search
Artificial Intelligence
2021-04-05 v1
Abstract
We present AlphaChute: a state-of-the-art algorithm that achieves superhuman performance in the ancient game of Chutes and Ladders. We prove that our algorithm converges to the Nash equilibrium in constant time, and therefore is -- to the best of our knowledge -- the first such formal solution to this game. Surprisingly, despite all this, our implementation of AlphaChute remains relatively straightforward due to domain-specific adaptations. We provide the source code for AlphaChute here in our Appendix.
Keywords
Cite
@article{arxiv.2104.00698,
title = {Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search},
author = {Dylan Ashley and Anssi Kanervisto and Brendan Bennett},
journal= {arXiv preprint arXiv:2104.00698},
year = {2021}
}