Estimating the Rank of Submitters of DAIHINMIN by Neural Networks

Abstract

DAIHINMIN is a kind of card game that is played in Japan. It is known that there are various local rules. It is common to aim to get rid of it quickly. It is a game played by multiple people, and it is classified as a multiplayer incomplete information game because the opponent's hand is not open. It is always 1 in such a card game. It is difficult to play aiming for rank. Therefore, the purpose of this research is to dynamically estimate the ranking that can be achieved from one's hand and the state of the field.