Zweistein: A Dynamic Programming Evaluation Function for Einstein W\"urfelt Nicht!

TL;DR

Zweistein is a data-driven dynamic programming evaluation function for Einstein W"urfelt Nicht! that outperforms traditional methods and won first place in the TCGA 2023 competition.

Contribution

It introduces a novel, data-centric evaluation function that eliminates parameter tuning and captures game state effectively.

Findings

Outperforms traditional evaluation functions

Wins first place in TCGA 2023 competition

Uses a distance vector to represent game state

Abstract

This paper introduces Zweistein, a dynamic programming evaluation function for Einstein W\"urfelt Nicht! (EWN). Instead of relying on human knowledge to craft an evaluation function, Zweistein uses a data-centric approach that eliminates the need for parameter tuning. The idea is to use a vector recording the distance to the corner of all pieces. This distance vector captures the essence of EWN. It not only outperforms many traditional EWN evaluation functions but also won first place in the TCGA 2023 competition.