AI in (and for) Games

• URL: http://arxiv.org/abs/2105.03123v1
• Date: Fri, 7 May 2021 08:57:07 GMT
• Title: AI in (and for) Games
• Authors: Kostas Karpouzis and George Tsatiris
• Abstract summary: This chapter outlines the relation between artificial intelligence (AI) / machine learning (ML) algorithms and digital games. On one hand, AI/ML researchers can generate large, in-the-wild datasets of human affective activity, player behaviour. On the other hand, 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.
• Score: 0.9920773256693857
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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