This paper presents the XML-based Video Game Description Language (XVGDL), a new language for specifying Video games which is based on the Extensible Markup Language (XML). The proposal is portable and extensible, and allows games to not only be defined at engine level but also includes specific features that can lead the game design process whilst simultaneously reducing the gap between game specification and its corresponding game implementation. XVGDL is as generic as possible, making it possible to describe different genres of games. This paper focuses on presenting the basis of the language. The paper describes the syntax as well as the components of XVGDL, and provides examples of their use. Defining games via XML structures provides all the advantages of the management of XML files and opens up interesting lines of research. Our proposal provides a number of novel features. So, XVGDL game definitions can be managed as any other XML file, which means that it can be automatically handled by any XML file management software. Another interesting feature is that XVGDL can specify game components (e.g., game Artificial), in-game processes (e.g., the procedural generation of maps) or in-game events (e.g., the checking of the conditions to end a game match) via the association with external (possibly non-XML) files. Moreover, XVGDL files can be easily validated as any XML file what means that validations against a particular Document Type Definition (DTD) or XML Schema Definition (XSD) are possible. In addition, the paper presents a first prototype implementation of a (text-based) interpreter that allows XVGDL game specifications as a playable game to be executed. This tool not only validates our proposal but also represents a first step towards smoothing the path to obtaining an executable version of a game from its game specification.INDEX TERMS Video game description language, extensible markup language, XML, game design, game tools.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.