Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search release_kolmfhs7hbbpbdikjfao4k4eym

by Dylan Ashley, Anssi Kanervisto, Brendan Bennett

Released as a article .

2021  

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.
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Date   2021-04-01
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arXiv  2104.00698v1
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