在Roguelike游戏中使用细胞自动机和Poisson磁盘采样来生成地牢的房间

Nur Muhammad Husnul Habib Yahya, Hadziq Fabroyir, D. Herumurti, Imam Kuswardayan, S. Arifiani
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引用次数: 0

摘要

程序内容生成(PCG)让游戏开发者能够更轻松地创造游戏世界。细胞自动机(CA)是众多PCG算法中的一种。在本研究中,CA与泊松磁盘采样(PDS)一起用于生成roguelike游戏中的二维地下城。改进了PDS以适应网格环境,提高了计算效率。游戏中生成的每个房间都是相互连接的。所有的房间合在一起形成了一个地牢。房间之间的连接使用深度优先搜索(DFS)算法构建,这是迷宫生成中常用的算法。创造出来的地下城变成了游戏中的世界。玩家可以探索地下城并征服它们并收集资源。然后,玩家可以使用这些资源来升级自己的角色。根据研究评估,仅使用CA不足以生成具有特定设计的地下城。要求某些管道调整和控制最终结果。尽管增加了所有的流水线,但算法的运行速度仍然足够快,大约为73毫秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dungeon's Room Generation Using Cellular Automata and Poisson Disk Sampling in Roguelike Game
Procedural Content Generation (PCG) allows game developers to create worlds in games easier compared with creating them manually. One of many PCG algorithms is Cellular Automata (CA). CA was used in this research together with Poisson Disk Sampling (PDS) to generate two-dimensional dungeons in a roguelike game. PDS was modified to adapt to a grid-based environment to increase computation's efficiency. Each room generated in the game was connected to each other. Together, all the rooms created a dungeon. The connections between the rooms were architected using Depth First Search (DFS) algorithm as commonly used in maze generation. The created dungeons became the world in the game. Players could explore the dungeons to conquer them and collect resources. Then, players could spend the resources to upgrade their character. According to the research evaluation, using only CA was not sufficient to generate dungeons with specific designs. Certain pipelines were demanded to adjust and to control the end results. The algorithm still run adequately fast, which was around 73 milliseconds, despite all the pipeline additions.
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