Personas versus clones for player decision modeling

Christoffer Holmgård; Antonios Liapis; Julian Togelius; Georgios N. Yannakakis

doi:10.1007/978-3-662-45212-7_20

Personas versus clones for player decision modeling

Christoffer Holmgård, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	159-166
Number of pages	8
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8770
DOIs	https://doi.org/10.1007/978-3-662-45212-7_20
State	Published - 2014

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-662-45212-7_20

Cite this

@article{8fac7aaa8ea04cd69188255effe768a7,

title = "Personas versus clones for player decision modeling",

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.",

author = "Christoffer Holmg{\aa}rd and Antonios Liapis and Julian Togelius and Yannakakis, {Georgios N.}",

note = "Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2014.",

year = "2014",

doi = "10.1007/978-3-662-45212-7_20",

language = "English (US)",

volume = "8770",

pages = "159--166",

journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

issn = "0302-9743",

publisher = "Springer Science and Business Media Deutschland GmbH",

}

TY - JOUR

T1 - Personas versus clones for player decision modeling

AU - Holmgård, Christoffer

AU - Liapis, Antonios

AU - Togelius, Julian

AU - Yannakakis, Georgios N.

N1 - Publisher Copyright: © IFIP International Federation for Information Processing 2014.

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84921501208&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84921501208&partnerID=8YFLogxK

U2 - 10.1007/978-3-662-45212-7_20

DO - 10.1007/978-3-662-45212-7_20

M3 - Article

AN - SCOPUS:84921501208

SN - 0302-9743

VL - 8770

SP - 159

EP - 166

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -

Personas versus clones for player decision modeling

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this