Emotion in Games

Yannakakis, Georgios N.; Karpouzis, Kostas; Paiva, Ana; Hudlická, Eva

doi:10.1007/978-3-642-24571-8_62

Cited by 28 publications

(32 citation statements)

References 96 publications

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“…Some authors suggest, that learning per se for humans is an enjoyable activity, and that (video) games are enjoyable specifically due to the learning principles they are usually based on (Gee, 2013). Above all, games evoke emotional experiences, which, again, per se for humans is a strong motivation (Geher, 2018;Yannakakis & Paiva, 2014).…”

Section: Theoretical Foundationsmentioning

confidence: 99%

Participation game

Prilenska

2021

plaNext

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Civic engagement in decision-making concerning the built environment has become a widely acknowledged practice. Today this is no longer about the dilemma of civic engagement, but rather about the best strategy for the purpose. Games and gamified applications are gaining popularity as efficient tools for civic engagement, which attract and retain participants, as well as foster learning and experimentation. The article presents the case of a role-play urban design game, Participation Game, which was developed in the iterative design process. The initial prototype of the game was transformed from session to session based on the player feedback, collected through questionnaires and debriefings, as well as the analysis of video recordings of game sessions. The overarching goals of the game were, firstly, to familiarise the audience with public hearings of urban design related projects, and, secondly, to find out how the changes in the setup of the game influence the player experience and the outcomes. The findings indicate that game setup limits the opportunities for discussion, and might even steer it towards desirable (for game authors) outcomes.

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Section: Theoretical Foundationsmentioning

confidence: 99%

Participation game

Prilenska

2021

plaNext

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“…The research area of Game AI is centered in computer science, but influenced by other disciplines as i.e. psychology, especially when it comes to handling humans and their emotions [89,90]. Furthermore, (computational) art and creativity (for PCG), game studies (formal models of play) and game design are important neighboring disciplines.…”

Section: Journals Conferences and Competitionsmentioning

confidence: 99%

From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI

Risi

Preuß

2020

Künstl Intell

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This paper reviews the field of Game AI, which not only deals with creating agents that can play a certain game, but also with areas as diverse as creating game content automatically, game analytics, or player modelling. While Game AI was for a long time not very well recognized by the larger scientific community, it has established itself as a research area for developing and testing the most advanced forms of AI algorithms and articles covering advances in mastering video games such as StarCraft 2 and Quake III appear in the most prestigious journals. Because of the growth of the field, a single review cannot cover it completely. Therefore, we put a focus on important recent developments, including that advances in Game AI are starting to be extended to areas outside of games, such as robotics or the synthesis of chemicals. In this article, we review the algorithms and methods that have paved the way for these breakthroughs, report on the other important areas of Game AI research, and also point out exciting directions for the future of Game AI.

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“…Such models are often built using machine learning methods where data consisting of some aspect of the game or player-game interaction is associated with labels derived from some assessment of player experience or affect, gathered for example from physiological measurements or questionnaires [55]. However, the area of player modeling is also concerned with structuring observed player behavior even when no correlates to experience are available, e.g.…”

Section: Player Modelingmentioning

confidence: 99%

A Panorama of Artificial and Computational Intelligence in Games

Yannakakis

Togelius

2015

IEEE Trans. Comput. Intell. AI Games

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133

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Abstract-This paper attempts to give a high-level overview of the field of artificial and computational intelligence (AI/CI) in games, with particular reference to how the different core research areas within this field inform and interact with each other, both actually and potentially. We identify ten main research areas within this field: NPC behavior learning, search and planning, player modeling, games as AI benchmarks, procedural content generation, computational narrative, believable agents, AI-assisted game design, general game artificial intelligence and AI in commercial games. We view and analyze the areas from three key perspectives: (1) the dominant AI method(s) used under each area; (2) the relation of each area with respect to the end (human) user; and (3) the placement of each area within a human-computer (player-game) interaction perspective. In addition, for each of these areas we consider how it could inform or interact with each of the other areas; in those cases where we find that meaningful interaction either exists or is possible, we describe the character of that interaction and provide references to published studies, if any. We believe that this paper improves understanding of the current nature of the game AI/CI research field and the interdependences between its core areas by providing a unifying overview. We also believe that the discussion of potential interactions between research areas provides a pointer to many interesting future research projects and unexplored subfields.

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Emotion in Games

Cited by 28 publications

References 96 publications

Participation game

Participation game

From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI

A Panorama of Artificial and Computational Intelligence in Games

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