An approach to human-like associations based on AI player creation for the picture-guessing card game Dixit

Abstract

This paper describes our study of AI player creation for the picture-guessing card game Dixit. In the game, the active player makes up a phrase (or sentence) that describes the image on one of her hand. The relation between the image and the phrase had better be moderate as she scores nothing if either all other players or no player guess correctly. As an extension of the previous research, we propose a method to give multiple meanings to images by selecting words whose vectors are similar to the result of adding vectors representing each group of words in the image. It was demonstrated through post-experimental questionnaires that more human-like associations were made compared to the previous research. We also inferred that humans can successfully associate words with low relevance to the image through two-step association. Currently, we are adding usable parts of speech and comparing the language models to implement two-step association.