This chapter outlines the relation between artificial intelligence (AI) / machine learning (ML) algorithms and digital games. This relation is two-fold: on one hand, AI/ML researchers can generate large, in-the-wild datasets of human affective activity, player behaviour (i.e. actions within the game world), commercial behaviour, interaction with graphical user interface elements or messaging with other players, while games can utilise intelligent algorithms to automate testing of game levels, generate content, develop intelligent and responsive non-player characters (NPCs) or predict and respond player behaviour across a wide variety of player cultures. In this work, we discuss some of the most common and widely accepted uses of AI/ML in games and how intelligent systems can benefit from those, elaborating on estimating player experience based on expressivity and performance, and on generating proper and interesting content for a language learning game.
翻译:本章概述了人工智能(AI)/机器学习算法和数字游戏之间的关系。这一关系有两个方面:一方面,AI/ML研究人员可以产生大量关于人类感官活动、玩家行为(即游戏世界内的行动)、商业行为、与图形用户界面要素的互动或与其他玩家的电文交流,而游戏可以利用智能算法使游戏水平测试自动化,生成内容,开发智能和反应灵敏的非玩家字符(NPCs)或预测和回应各种玩家行为。在这项工作中,我们讨论了游戏中最常见和广泛接受的AI/ML的一些最常用的用途,以及智能系统如何从这些用途中受益,阐述根据表现和性能估计玩家经验,以及为语言学习游戏创造适当和有趣的内容。