Procedural Content Generation for Real-Time Strategy Games

R. Lara-Cabrera, M. Nogueira, C. Cotta, Antonio J. Fernández
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引用次数: 7

Abstract

Videogames are one of the most important and profitable sectors in the industry of entertainment. Nowadays, the creation of a videogame is often a large-scale endeavor and bears many similarities with, e.g., movie production. On the central tasks in the development of a videogame is content generation, namely the definition of maps, terrains, non-player characters (NPCs) and other graphical, musical and AI-related components of the game. Such generation is costly due to its complexity, the great amount of work required and the need of specialized manpower. Hence the relevance of optimizing the process and alleviating costs. In this sense, procedural content generation (PCG) comes in handy as a means of reducing costs by using algorithmic techniques to automatically generate some game contents. PCG also provides advantages in terms of player experience since the contents generated are typically not fixed but can vary in different playing sessions, and can even adapt to the player herself. For this purpose, the underlying algorithmic technique used for PCG must be also flexible and adaptable. This is the case of computational intelligence in general and evolutionary algorithms in particular. In this work we shall provide an overview of the use of evolutionary intelligence for PCG, with special emphasis on its use within the context of real- time strategy games. We shall show how these techniques can address both playability and aesthetics, as well as improving the game AI. PURRED on by the emergence of the videogame industry as the main component of the entertainment industry has motivated, research on videogames has acquired increasing notoriety during the last years. Such research spans many areas such as marketing and gamification, psychology and player satisfaction, computational intelligence, education and health (serious games) and computer graphics, just to cite a few. This diversification of research areas is largely motivated by a shift in the priorities of the video game industry: while games used to rely heavily on their graphical quality, other features such as the music, the player immersion into the game and interesting storyline have gained enormous importance. To cope with the plethora of new interesting challenges in the area of
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即时策略游戏的程序内容生成
电子游戏是娱乐行业中最重要、最赚钱的领域之一。如今,电子游戏的创造通常是一项大规模的努力,并且与电影制作有许多相似之处。电子游戏开发的核心任务是内容生成,即定义地图、地形、非玩家角色(npc)以及游戏的其他图像、音乐和ai相关组件。由于生产过程复杂,工作量大,需要专门的人力,所以成本很高。因此,优化流程和降低成本具有重要意义。从这个意义上说,程序内容生成(PCG)作为一种通过使用算法技术自动生成某些游戏内容而降低成本的方法非常有用。PCG在玩家体验方面也具有优势,因为生成的内容通常不是固定的,而是在不同的游戏过程中发生变化,甚至可以适应玩家自身。为此,用于PCG的底层算法技术也必须具有灵活性和适应性。这是计算智能的一般情况,尤其是进化算法。在这项工作中,我们将概述进化智能在PCG中的应用,特别强调它在实时策略游戏中的应用。我们将展示这些技术如何解决可玩性和美学问题,以及如何改进游戏AI。随着电子游戏产业作为娱乐产业的主要组成部分的出现,关于电子游戏的研究在过去几年里获得了越来越多的名声。这类研究涵盖了许多领域,如市场营销和游戏化、心理学和玩家满意度、计算智能、教育和健康(严肃游戏)以及计算机图形学等。这种研究领域的多样化很大程度上是由电子游戏行业优先级的转变所推动的:虽然游戏过去严重依赖于它们的图像质量,但音乐、玩家对游戏的沉浸感和有趣的故事情节等其他功能变得非常重要。来应对领域中大量有趣的新挑战
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