Research on Fight the Landlords’ Single Card Guessing Based on Deep Learning

Abstract

In the real world, most of the information is non-accurate and non-complete. The model which guesses the number of the cards is a predictive model based on incomplete information. Players need to know a relatively small amount of information on the card to make accurate predictions. Based on the deep learning method, this paper studies single card speculation method on Fight the landlords game. Located in the perspective of the landlord, the model based on a certain amount of historical card information extracts the dominant features, and makes a reasonable prediction for peasant players’ hands. The algorithm uses the CNN model to design the game turn-based body, single player’s history and the brand-out process of three players simultaneously in the model input matrix. It extracts the characteristics of the landlord playing cards, and predicts the situation of the hand of two peasant players up and down. The experimental results show that the result of single card guess basically accords with the habit of human playing cards.