Review of intrinsic motivation in simulation-based game testing

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Standard

Review of intrinsic motivation in simulation-based game testing. / Roohi, Shaghayegh; Takatalo, Jari; Guckelsberger, Christian; Hämäläinen, Perttu.

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. ACM, 2018.

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Harvard

Roohi, S, Takatalo, J, Guckelsberger, C & Hämäläinen, P 2018, Review of intrinsic motivation in simulation-based game testing. julkaisussa Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. ACM, Montreal, Kanada, 21/04/2018. https://doi.org/10.1145/3173574.3173921

APA

Roohi, S., Takatalo, J., Guckelsberger, C., & Hämäläinen, P. (2018). Review of intrinsic motivation in simulation-based game testing. teoksessa Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI ACM. https://doi.org/10.1145/3173574.3173921

Vancouver

Roohi S, Takatalo J, Guckelsberger C, Hämäläinen P. Review of intrinsic motivation in simulation-based game testing. julkaisussa Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. ACM. 2018 https://doi.org/10.1145/3173574.3173921

Author

Roohi, Shaghayegh ; Takatalo, Jari ; Guckelsberger, Christian ; Hämäläinen, Perttu. / Review of intrinsic motivation in simulation-based game testing. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. ACM, 2018.

Bibtex - Lataa

@inproceedings{639a09fa736f4a0086400e0ed87816b3,
title = "Review of intrinsic motivation in simulation-based game testing",
abstract = "This paper presents a review of intrinsic motivation in player modeling, with a focus on simulation-based game testing. Modern AI agents can learn to win many games; from a game testing perspective, a remaining research problem is how to model the aspects of human player behavior not explained by purely rational and goal-driven decision making. A major piece of this puzzle is constituted by intrinsic motivations, i.e., psychological needs that drive behavior without extrinsic reinforcement such as game score. We first review the common intrinsic motivations discussed in player psychology research and artificial intelligence, and then proceed to systematically review how the various motivations have been implemented in simulated player agents. Our work reveals that although motivations such as competence and curiosity have been studied in AI, work on utilizing them in simulation-based game testing is sparse, and other motivations such as social relatedness, immersion, and domination appear particularly underexplored.",
keywords = "Artificial intelligence, Emotion, Game testing, Intrinsic motivation, Player modeling",
author = "Shaghayegh Roohi and Jari Takatalo and Christian Guckelsberger and Perttu H{\"a}m{\"a}l{\"a}inen",
year = "2018",
month = "4",
day = "20",
doi = "10.1145/3173574.3173921",
language = "English",
booktitle = "Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems",
publisher = "ACM",

}

RIS - Lataa

TY - GEN

T1 - Review of intrinsic motivation in simulation-based game testing

AU - Roohi, Shaghayegh

AU - Takatalo, Jari

AU - Guckelsberger, Christian

AU - Hämäläinen, Perttu

PY - 2018/4/20

Y1 - 2018/4/20

N2 - This paper presents a review of intrinsic motivation in player modeling, with a focus on simulation-based game testing. Modern AI agents can learn to win many games; from a game testing perspective, a remaining research problem is how to model the aspects of human player behavior not explained by purely rational and goal-driven decision making. A major piece of this puzzle is constituted by intrinsic motivations, i.e., psychological needs that drive behavior without extrinsic reinforcement such as game score. We first review the common intrinsic motivations discussed in player psychology research and artificial intelligence, and then proceed to systematically review how the various motivations have been implemented in simulated player agents. Our work reveals that although motivations such as competence and curiosity have been studied in AI, work on utilizing them in simulation-based game testing is sparse, and other motivations such as social relatedness, immersion, and domination appear particularly underexplored.

AB - This paper presents a review of intrinsic motivation in player modeling, with a focus on simulation-based game testing. Modern AI agents can learn to win many games; from a game testing perspective, a remaining research problem is how to model the aspects of human player behavior not explained by purely rational and goal-driven decision making. A major piece of this puzzle is constituted by intrinsic motivations, i.e., psychological needs that drive behavior without extrinsic reinforcement such as game score. We first review the common intrinsic motivations discussed in player psychology research and artificial intelligence, and then proceed to systematically review how the various motivations have been implemented in simulated player agents. Our work reveals that although motivations such as competence and curiosity have been studied in AI, work on utilizing them in simulation-based game testing is sparse, and other motivations such as social relatedness, immersion, and domination appear particularly underexplored.

KW - Artificial intelligence

KW - Emotion

KW - Game testing

KW - Intrinsic motivation

KW - Player modeling

UR - http://www.scopus.com/inward/record.url?scp=85046963685&partnerID=8YFLogxK

U2 - 10.1145/3173574.3173921

DO - 10.1145/3173574.3173921

M3 - Conference contribution

BT - Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

PB - ACM

ER -

ID: 21505339