{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T21:18:05Z","timestamp":1775251085918,"version":"3.50.1"},"reference-count":48,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1109\/cig.2018.8490442","type":"proceedings-article","created":{"date-parts":[[2018,10,15]],"date-time":"2018-10-15T23:37:41Z","timestamp":1539646661000},"page":"1-8","source":"Crossref","is-referenced-by-count":64,"title":["Human-Like Playtesting with Deep Learning"],"prefix":"10.1109","author":[{"given":"Stefan Freyr","family":"Gudmundsson","sequence":"first","affiliation":[]},{"given":"Philipp","family":"Eisen","sequence":"additional","affiliation":[]},{"given":"Erik","family":"Poromaa","sequence":"additional","affiliation":[]},{"given":"Alex","family":"Nodet","sequence":"additional","affiliation":[]},{"given":"Sami","family":"Purmonen","sequence":"additional","affiliation":[]},{"given":"Bartlomiej","family":"Kozakowski","sequence":"additional","affiliation":[]},{"given":"Richard","family":"Meurling","sequence":"additional","affiliation":[]},{"given":"Lele","family":"Cao","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"Simulating human game play for level difficulty estimation with convolutional neural networks","author":"eisen","year":"2017","journal-title":"Master’s thesis"},{"key":"ref38","author":"krizhevsky","year":"2012","journal-title":"ImageNet Classification with Deep Convolutional Neural Networks"},{"key":"ref33","author":"peng","year":"2017","journal-title":"Multiagent bidirectionally-coordinated nets for learning to play StarCraft combat games"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1038\/nature24270","article-title":"Mastering the game of go without human knowledge","volume":"550","author":"silver","year":"2017","journal-title":"Nature"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2014.2307272"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1007\/978-3-540-75538-8_7","article-title":"Efficient selectivity and backup operators in Monte-Carlo tree search","volume":"4630","author":"coulom","year":"2007","journal-title":"Computers and Games"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273531"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2011.03.007"},{"key":"ref35","first-page":"1","article-title":"Recent advances in general game playing","volume":"2015","author":"park","year":"2015","journal-title":"The Scientific World Journal"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2012.2186810"},{"key":"ref10","first-page":"1766","article-title":"Training deep convolutional neural networks to play go","author":"clark","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref40","article-title":"Predicting game level difficulty using deep neural networks","author":"purmonen","year":"2017","journal-title":"Master’s thesis"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1038\/nature16961","article-title":"Mastering the game of Go with deep neural networks and tree search","volume":"529","author":"silver","year":"2016","journal-title":"Nature"},{"key":"ref12","first-page":"292","article-title":"Move prediction in Gomoku using deep learning","author":"shao","year":"2017","journal-title":"Proceedings of IEEE Youth Academic Annual Conference of Chinese Association of Automation (YAC)"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3912"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2014.6932911"},{"key":"ref16","first-page":"159","article-title":"Personas versus clones for player decision modeling","author":"holmg\u00e5rd","year":"2014","journal-title":"Entertainment Computing – ICEC 2014"},{"key":"ref17","article-title":"Automated playtesting with procedural personas through MCTS with evolved heuristics","volume":"abs 1802 6881","author":"holmg\u00e5rd","year":"2018","journal-title":"CoRR"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/640725"},{"key":"ref19","first-page":"305","article-title":"Predicting player experience without the player.: An exploratory study","author":"guckelsberger","year":"0"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1007\/978-3-319-16549-3_30","article-title":"General video game evaluation using relative algorithm performance profiles","author":"nielsen","year":"2015","journal-title":"Proceedings of the European Conference on Applications of Evolutionary Computation"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4471-4769-5"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2016.7860398"},{"key":"ref3","first-page":"2511","article-title":"Challenge in digital games: Towards developing a measurement tool","author":"denisova","year":"0"},{"key":"ref6","article-title":"Automatic Playtesting for Game Parameter Tuning via Active Learning","author":"zook","year":"2014","journal-title":"Foundations of Digital Games"},{"key":"ref29","first-page":"122","article-title":"Matching games and algorithms for general video game playing","author":"bontrager","year":"2016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1621841.1621878"},{"key":"ref8","article-title":"Crushing Candy Crush: Predicting Human Success Rate in a Mobile Game using Monte-Carlo Tree Search","author":"poromaa","year":"2017","journal-title":"Master’s thesis"},{"key":"ref7","article-title":"Exploring game space using survival analysis","author":"isaksen","year":"2015","journal-title":"Proceedings of the 10th International Conference on the Foundations of Digital Games"},{"key":"ref2","first-page":"1","article-title":"Free-to-Play Games: Professionals’ Perspectives","author":"alha","year":"2014","journal-title":"Proceedings of Nordic DiGRA"},{"key":"ref9","article-title":"AI as Evaluator: Search Driven Playtesting in Game Design","author":"silva","year":"2016","journal-title":"Proceedings of AAAI"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2016.09.004"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(98)00007-3"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2271738"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref48","article-title":"Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network","author":"volz","year":"2018","journal-title":"ArXiv e-prints"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2014.6932868"},{"key":"ref47","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-42716-4","author":"shaker","year":"2016","journal-title":"Procedural Content Generation in Games"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1609\/aiide.v8i1.12527","article-title":"Fast heuristic search for rts game combat scenarios","author":"churchill","year":"2012","journal-title":"Proceedings of the 8th AIIDE"},{"key":"ref42","first-page":"769","article-title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","volume":"51","author":"simonyan","year":"2014","journal-title":"Information and Software Technology"},{"key":"ref24","doi-asserted-by":"crossref","DOI":"10.1609\/aiide.v12i1.12858","article-title":"Combining gameplay data with monte carlo tree search to emulate human play","author":"devlin","year":"2016"},{"key":"ref41","article-title":"Network in network","author":"lin","year":"2014","journal-title":"Proceedings of ICL"},{"key":"ref23","article-title":"Monte-carlo tree search for simulation-based strategy analysis","author":"zook","year":"2015","journal-title":"Proceedings of the 10th Conference on the Foundations of Digital Games"},{"key":"ref44","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proceedings of International Conference on Machine Learning"},{"key":"ref26","first-page":"2514","article-title":"Modifying MCTS for Human-like General Video Game Playing","author":"khalifa","year":"2016","journal-title":"Proceedings of IJCAI"},{"key":"ref43","first-page":"1","article-title":"Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)","author":"clevert","year":"2016","journal-title":"Proceedings of ICL"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2015.7317924"}],"event":{"name":"2018 IEEE Conference on Computational Intelligence and Games (CIG)","location":"Maastricht","start":{"date-parts":[[2018,8,14]]},"end":{"date-parts":[[2018,8,17]]}},"container-title":["2018 IEEE Conference on Computational Intelligence and Games (CIG)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8473398\/8490359\/08490442.pdf?arnumber=8490442","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T20:07:57Z","timestamp":1775246877000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8490442\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/cig.2018.8490442","relation":{},"subject":[],"published":{"date-parts":[[2018,8]]}}}