Makarovych, Sasha, Canossa, Alessandro, Togelius, Julian et al. (1 more author) (Accepted: 2018) Like a DNA string:Sequence-based Player Profiling in Tom Clancy’s The Division. In: Artificial Intelligence and Interactive Digital Entertainment Conference, 13-17 Nov 2018. (In Press)
Abstract
In this paper we present an approach for using sequence analysis to model player behavior. This approach is designed to work in game development contexts, integrating production teams and delivering profiles that inform game design. We demonstrate the method via a case study of the game Tom Clancy’s The Division, which with its 20 million players represents a major current commercial title. The approach presented provides a mixed-methods framework, combining qualitative knowledge elicitation and workshops with largescale telemetry analysis, using sequence mining and clustering to develop detailed player profiles showing the core gameplay loops of The Division’s players.
Metadata
Item Type: | Conference or Workshop Item |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2018, Association for the Advancement of Artificial Intelligence. |
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 17 Oct 2018 09:50 |
Last Modified: | 21 Jan 2025 18:29 |
Status: | In Press |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:137047 |