自动视频游戏参数调整与XVGDL+

J. R. Quiñones, Antonio J. Fernández
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引用次数: 2

摘要

通常,为了在游戏调整或平衡过程中提供反馈,需要人类的参与。此外,这通常是一个迭代过程,在这个过程中需要进行游戏测试,以及收集所有重要信息以改进和调整游戏组件规范的人类互动。本文提出了一种加速这一过程并显著降低其成本的机制,并提供了使用搜索算法和人工智能(AI)技术执行游戏参数调整和游戏平衡的解决方案。这个过程以完全自动化的方式执行,只需要用特定的电子游戏描述语言编写游戏规范。自动游戏测试和游戏反馈信息分析与执行游戏参数的调整和平衡有关,从而为优化电子游戏规范的问题提供解决方案。最近,一种新的基于可扩展标记语言(XML)的电子游戏指定语言XVGDL出现了。本文使用了XVGDL+,这是该语言的扩展,它包含了新的组件来在视频游戏规范中指定每次游戏执行后要评估的理想目标或需求。本文还介绍了一个游戏引擎的原型实现(称为XGE+)。这个游戏引擎不仅可以执行XVGDL+游戏规范,还可以在游戏完成后提供反馈信息。本文证明了xgdl +与XGE+的结合为解决游戏AI研究问题提供了一种强大的机制,在这种情况下,视频游戏参数的游戏调整,相对于初始优化目标。这些目标(游戏邦注:这是本文提出的建议的特点之一)包含在游戏规范中,将过程的输入最小化。为了证明这一点,我们进行了两个实验,通过爬山局部搜索方法,以全自动的方式优化了用XVGDL编写的游戏规范。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated video game parameter tuning with XVGDL+
Usually, human participation is required in order to provide feedback during the game tuning or balancing process. Moreover, this is commonly an iterative process in which play-testing is required as well as human interaction for gathering all important information to improve and tune the game components’ specification. In this paper, a mechanism is proposed to accelerate this process and reduce significantly the costs of it, contributing with a solution to perform the game parameter tuning and game balancing using search algorithms and artificial intelligence (AI) techniques. The process is executed in a fully automated way, and just requires a game specification written in a particular video game description language. Automated play-testing, and game’s feedback information analysis, are related to perform game parameters’ tuning and balancing, leading to offer a solution for the problem of optimizing a video game specification. Recently, XVGDL, a new language for specifying video games which is based on the eXtensible Markup Language (XML), has been presented. This paper uses XVGDL+, an extension of this lan- guage that incorporates new components to specify, within the video game specification, desirable goals or requirements to be evaluated after each game execution. A prototypical implementation of a Game Engine (termed XGE+) was also presented. This game engine not only enables the execution of an XVGDL+ game specification but also provides feedback information once the game has finished. The paper demonstrates that the combination of XVGDL+ with XGE+ offers a powerful mechanism for helping solving game AI research problems, in this case, the game tuning of video game parameters, with respect to initial optimization goals. These goals, as one of the particularities of the proposal presented here, are included within the game specification, minimizing the input of the process. As a practical proof of it, two experiments have been conducted to optimize a game specification written in XVGDL via a hill climbing local search method, in a fully automated way.
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