TY - JOUR
T1 - Player behavioural modelling for video games
AU - Bakkes, Sander C.J.
AU - Spronck, Pieter H.M.
AU - van Lankveld, Giel
N1 - Funding Information:
Part of this research was funded by Agentschap.nl, in the context of the EOS Project Persuasive Agents, and the SIA RAAK Project Smart Systems for Smart Services.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2012/8
Y1 - 2012/8
N2 - Player behavioural modelling has grown from a means to improve the playing strength of computer programs that play classic games (e.g., chess), to a means for impacting the player experience and satisfaction in video games, as well as in cross-domain applications such as interactive storytelling. In this context, player behavioural modelling is concerned with two goals, namely (1) providing an interesting or effective game AI on the basis of player models and (2) creating a basis for game developers to personalise gameplay as a whole, and creating new user-driven game mechanics. In this article, we provide an overview of player behavioural modelling for video games by detailing four distinct approaches, namely (1) modelling player actions, (2) modelling player tactics, (3) modelling player strategies, and (4) player profiling. We conclude the article with an analysis on the applicability of the approaches for the domain of video games.
AB - Player behavioural modelling has grown from a means to improve the playing strength of computer programs that play classic games (e.g., chess), to a means for impacting the player experience and satisfaction in video games, as well as in cross-domain applications such as interactive storytelling. In this context, player behavioural modelling is concerned with two goals, namely (1) providing an interesting or effective game AI on the basis of player models and (2) creating a basis for game developers to personalise gameplay as a whole, and creating new user-driven game mechanics. In this article, we provide an overview of player behavioural modelling for video games by detailing four distinct approaches, namely (1) modelling player actions, (2) modelling player tactics, (3) modelling player strategies, and (4) player profiling. We conclude the article with an analysis on the applicability of the approaches for the domain of video games.
KW - Adaptive behaviour
KW - Player behavioural modelling
KW - Video game AI
UR - http://www.scopus.com/inward/record.url?scp=84865188740&partnerID=8YFLogxK
U2 - 10.1016/j.entcom.2011.12.001
DO - 10.1016/j.entcom.2011.12.001
M3 - Article
AN - SCOPUS:84865188740
SN - 1875-9521
VL - 3
SP - 71
EP - 79
JO - Entertainment Computing
JF - Entertainment Computing
IS - 3
ER -