|
JAIST Repository >
School of Transdisciplinary Science >
Articles >
Journal Articles >
Please use this identifier to cite or link to this item:
https://hdl.handle.net/10119/20015
|
| Title: | Using Reinforcement Learning to Generate Levels of Super Mario Bros. with Quality and Diversity |
| Authors: | Nam, Sang-Gyu
Hsueh, Chu-Hsuan
Rerkjirattikal, Pavinee
Ikeda, Kokolo |
| Keywords: | Reinforcement learning
procedural content generation
Super Mario Bros.
quality and diversity |
| Issue Date: | 2024-06-19 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Magazine name: | IEEE Transactions on Games |
| Volume: | 16 |
| Number: | 4 |
| Start page: | 807 |
| End page: | 820 |
| DOI: | 10.1109/TG.2024.3416472 |
| Abstract: | 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: | https://hdl.handle.net/10119/20015 |
| Material Type: | author |
| Appears in Collections: | d10-1. 雑誌掲載論文 (Journal Articles)
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| T-IKEDA-K-0930-1.pdf | | 7752Kb | Adobe PDF | View/Open |
|
All items in DSpace are protected by copyright, with all rights reserved.
|
