Abstract : The current paper investigates how to model human play styles. Building on decision and persona theory we evolve game playing agents representing human decision making styles. Two methods are developed, applied, and compared: procedural personas, based on utilities designed with expert knowledge, and clones, trained to reproduce play traces. Additionally, two metrics for comparing agent and human decision making styles are proposed and compared. Results indicate that personas evolved from designer intuitions can capture human decision making styles equally well as clones evolved from human play traces.
Type de document :
Communication dans un congrès
Yusuf Pisan; Nikitas M. Sgouros; Tim Marsh. 13th International Conference Entertainment Computing (ICEC), Oct 2014, Sydney, Australia. Springer, Lecture Notes in Computer Science, LNCS-8770, pp.159-166, 2014, Entertainment Computing – ICEC 2014. 〈10.1007/978-3-662-45212-7_20〉
https://hal.inria.fr/hal-01408517
Contributeur : Hal Ifip
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Soumis le : lundi 5 décembre 2016 - 09:42:07
Dernière modification le : lundi 5 décembre 2016 - 10:24:50
Document(s) archivé(s) le : lundi 20 mars 2017 - 16:08:34
Christoffer Holmgård, Antonios Liapis, Julian Togelius, Georgios Yannakakis. Personas versus Clones for Player Decision Modeling. Yusuf Pisan; Nikitas M. Sgouros; Tim Marsh. 13th International Conference Entertainment Computing (ICEC), Oct 2014, Sydney, Australia. Springer, Lecture Notes in Computer Science, LNCS-8770, pp.159-166, 2014, Entertainment Computing – ICEC 2014. 〈10.1007/978-3-662-45212-7_20〉. 〈hal-01408517〉
