Level Generation for Angry Birds with Sequential Autoencoder

DOI
  • TANABE Takumi
    University of Tsukuba RIKEN Center for Advanced Intelligence Project
  • FUKUCHI Kazuto
    University of Tsukuba RIKEN Center for Advanced Intelligence Project
  • SAKUMA Jun
    University of Tsukuba RIKEN Center for Advanced Intelligence Project
  • AKIMOTO Youhei
    University of Tsukuba RIKEN Center for Advanced Intelligence Project

Bibliographic Information

Other Title
  • Sequential Variational Autoencoderを用いたAngry Birdsのステージ生成

Description

<p>In this paper, we propose a deep generative model based level generation method for the video game Angry Birds. Although Angry Birds is a popular target for level generation, it is difficult to generate a stable level automatically because the level is governed by the gravity and there is a high degree of freedom in generating the level, and automatic generation using deep generative models is rarely done. In this study, we propose to encode levels sequentially and process them as text data, while existing methods process levels as images using a tile-based encoding method. The experimental results show that the existing methods fail to generate stable levels with high probability, while the proposed method succeeds in generating stable levels with high probability, and also generates levels with diversity.</p>

Journal

Keywords

Details 詳細情報について

Report a problem

Back to top