CADGame – Computer-Aided Game Design

@article{DBLP:journals/tciaig/GowBCCM12,
title = {Unsupervised Modeling of Player Style With LDA},
author = {Jeremy Gow and Robin Baumgarten and Paul A. Cairns and Simon Colton and Paul Miller},
url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/03/gow_tciaig12.pdf},
doi = {10.1109/TCIAIG.2012.2213600},
year = {2012},
date = {2012-01-01},
journal = {IEEE Trans. Comput. Intellig. and AI in Games},
volume = {4},
number = {3},
pages = {152--166},
abstract = {Computational analysis of player style has signifi- cant potential for video game design: it can provide insights into player behaviour, as well as the means to dynamically adapt a game to each individual’s style of play. To realise this potential, computational methods need to go beyond considerations of challenge and ability and account for aesthetic aspects of player style. We describe here a semi-automatic unsupervised learning approach to modelling player style using multi-class Linear Discriminant Analysis (LDA). We argue that this approach is widely applicable for modelling player style in a wide range of games, including commercial applications, and illustrate it with two case studies: the first for a novel arcade game called Snakeotron, the second for Rogue Trooper, a modern commercial third-person shooter video game.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@inproceedings{DBLP:conf/aiide/GowCCM12,
title = {Mining Rules from Player Experience and Activity Data},
author = {Jeremy Gow and Simon Colton and Paul A. Cairns and Paul Miller},
url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/03/gow_aiide12.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the Eighth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE-12, Stanford, California, October 8-12, 2012},
crossref = {DBLP:conf/aiide/2012},
abstract = {Feedback on player experience and behaviour can be invaluable to game designers, but there is need for specialised knowledge discovery tools to deal with high volume playtest data. We describe a study with a commercial third-person shooter, in which integrated player activity and experience data was captured and mined for design-relevant knowledge. We demonstrate that association rule learning and rule templates can be used to extract meaningful rules relating player activity and experience during combat. We found that the number, type and quality of rules varies between experiences, and is affected by feature distributions. Further work is required on rule selection and evaluation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{Gow2010PlayerExperience,
title = {Capturing Player Experience With Post-Game Commentaries},
author = {Jeremy Gow and Paul Cairns and Simon Colton and Paul Miller and Robin Baumgarten},
url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/gow_cgat10.pdf},
year = {2010},
date = {2010-10-01},
booktitle = {Proceedings 3rd International Conference on Computer Games, Multimedia & Allied Technology (CGAT 2010)},
abstract = {Player experience is at the heart of good game design, but designers typically have limited experience data to work with. Detailed and fine-grained accounts of gaming experience would be of great value to designers and researchers alike, but recording such data is a significant challenge. We describe an approach based on post-game player commentaries, retrospective verbal reports cued by video of the gaming session and a word list. A pilot study was carried out to capture player experience of a tutorial level for a third person shooter game. We show how the technique can be used to provide useful game design feedback.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}