|
JAIST Repository >
b. 情報科学研究科・情報科学系 >
b11. 会議発表論文・発表資料等 >
b11-1. 会議発表論文・発表資料 >
このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/18208
|
タイトル: | Generation of Diverse Stages in Turn-Based RPG using Reinforcement Learning |
著者: | Nam, SangGyu Ikeda, Kokolo |
発行日: | 2019-08-20 |
出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
誌名: | IEEE CONFERENCE ON GAMES (COG), London, UK, 20th August 2019 |
開始ページ: | 1 |
終了ページ: | 8 |
DOI: | 10.1109/CIG.2019.8848090 |
抄録: | In this study, procedural content generation (PCG) using reinforcement learning (RL) is focused. PCG is defined as the generation of game content tailored to the defined evaluation function using RL models, which is one of the examples of PCG via machine learning. Compared to other generation content areas such as computer vision and natural language process, supervised learning generative methods such as variational autoencoders, PixelCNN, and generative adversarial networks exhibit some difficulties for applications to the game area because during the development of a new game, the content data used for training is typically not sufficient. Hence, RL is considered to be used as a method for PCG. In particular, the stage of turn-based RPG is selected as our research target because it comprises discrete sections, and its parameters were closely related; hence, it is a challenge to generate desirable stages, and the main goal is to generate various stages guided by the designed evaluation function. Two RL models, Deep Q-Network and Deep Deterministic Policy Gradient, respectively, are selected, and the generated stages are evaluated as 0.78 and 0.85 by our designed function, respectively. By the application of the stochastic noise policy, diverse stages are successfully obtained, and those diversities are evaluated by the parameter mse and the different number of valid strategies. |
Rights: | This is the author's version of the work. Copyright (C) 2019 IEEE. IEEE CONFERENCE ON GAMES (COG). DOI: 10.1109/CIG.2019.8848090. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
URI: | http://hdl.handle.net/10119/18208 |
資料タイプ: | author |
出現コレクション: | b11-1. 会議発表論文・発表資料 (Conference Papers)
|
このアイテムのファイル:
ファイル |
記述 |
サイズ | 形式 |
I-IKEDA-K-3132.pdf | | 1336Kb | Adobe PDF | 見る/開く |
|
当システムに保管されているアイテムはすべて著作権により保護されています。
|