Expression of reflection-impulsivity for pokémon non player character by prior information in Bayesian estimation

Abstract

Pokemon is one of the most famous video games, which has more than 3.4 million players around the world. The interesting part of this game is to guess invisible information and the character of the opponent. However, existing Non Player Character (NPC) of this game is not a good alternative opponent to a human player because the NPC does not have variety of characteristics. In this paper, we propose a novel method to represent reflection - impulsivity characteristics of NPC by differences of the first stage prior distribution in Bayesian estimation used for decision-making of the NPC. In the experiment, we ask human players to take on three types of the proposed NPC and to answer the impression of those NPCs. As the result, the players feel different impressions from the three types of NPCs although they cannot identify the three types of the character (reflection - intermediate - impulsivity).