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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/10119/20015
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| タイトル: | Using Reinforcement Learning to Generate Levels of Super Mario Bros. with Quality and Diversity |
| 著者: | Nam, Sang-Gyu
Hsueh, Chu-Hsuan
Rerkjirattikal, Pavinee
Ikeda, Kokolo |
| キーワード: | Reinforcement learning
procedural content generation
Super Mario Bros.
quality and diversity |
| 発行日: | 2024-06-19 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | IEEE Transactions on Games |
| 巻: | 16 |
| 号: | 4 |
| 開始ページ: | 807 |
| 終了ページ: | 820 |
| DOI: | 10.1109/TG.2024.3416472 |
| 抄録: | Procedural content generation (PCG) is essential in game development, automating content creation to meet various criteria such as playability, diversity, and quality. This paper leverages reinforcement learning (RL) for PCG to generate Super Mario Bros levels. We formulate the problem into a Markov decision process (MDP), with rewards defined using player enjoyment-based evaluation functions. Challenges in level representation and difficulty assessment are addressed by conditional generative adversarial networks (CGAN) and human-like AI agents that mimic aspects of human input inaccuracies. This ensures that the generated levels are appropriately challenging from human perspectives. Furthermore, we enhance content quality through virtual simulation (VS), which assigns rewards to intermediate actions to address a credit assignment problem (CAP). We also ensure diversity through a diversity-aware greedy policy (DAGP), which chooses not-bad-but-distant actions based on Q-values. These processes ensure the production of diverse and high-quality Super Mario levels. Human subject evaluations revealed that levels generated from our approach exhibit natural connection, appropriate difficulty, non-monotony, and diversity, highlighting the effectiveness of our proposed methods. The novelty of our work lies in the innovative solutions we propose to address challenges encountered in employing PCGRL in Super Mario Bros, contributing to the field of PCG for game development. |
| Rights: | This is the author's version of the work. Copyright (C) 2024 IEEE. IEEE Transactions on Games. DOI: https://doi.org/10.1109/TG.2024.3416472. 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/10119/20015 |
| 資料タイプ: | author |
| 出現コレクション: | d10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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| T-IKEDA-K-0930-1.pdf | | 7752Kb | Adobe PDF | 見る/開く |
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