TY - GEN
T1 - Automated playtesting of matching tile games
AU - Mugrai, Luvneesh
AU - Silva, Fernando
AU - Holmgard, Christoffer
AU - Togelius, Julian
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Matching tile games are an extremely popular game genre. Arguably the most popular iteration, Match-3 games, are simple to understand puzzle games, making them great benchmarks for research. In this paper, we propose developing different procedural personas for Match-3 games in order to approximate different human playstyles to create an automated playtesting system. The procedural personas are realized through evolving the utility function for the Monte Carlo Tree Search agent. We compare the performance and results of the evolution agents with the standard Vanilla Monte Carlo Tree Search implementation as well as to a random move-selection agent. We then observe the impacts on both the game's design and the game design process. Lastly, a user study is performed to compare the agents to human play traces.
AB - Matching tile games are an extremely popular game genre. Arguably the most popular iteration, Match-3 games, are simple to understand puzzle games, making them great benchmarks for research. In this paper, we propose developing different procedural personas for Match-3 games in order to approximate different human playstyles to create an automated playtesting system. The procedural personas are realized through evolving the utility function for the Monte Carlo Tree Search agent. We compare the performance and results of the evolution agents with the standard Vanilla Monte Carlo Tree Search implementation as well as to a random move-selection agent. We then observe the impacts on both the game's design and the game design process. Lastly, a user study is performed to compare the agents to human play traces.
KW - Genetic Evolution
KW - Match-3
KW - Monte Carlo Tree Search
KW - Procedural Personas
UR - http://www.scopus.com/inward/record.url?scp=85073102111&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073102111&partnerID=8YFLogxK
U2 - 10.1109/CIG.2019.8848057
DO - 10.1109/CIG.2019.8848057
M3 - Conference contribution
AN - SCOPUS:85073102111
T3 - IEEE Conference on Computatonal Intelligence and Games, CIG
BT - IEEE Conference on Games 2019, CoG 2019
PB - IEEE Computer Society
T2 - 2019 IEEE Conference on Games, CoG 2019
Y2 - 20 August 2019 through 23 August 2019
ER -