TY - GEN
T1 - Dynamic game difficulty balancing in real time using evolutionary fuzzy cognitive maps
AU - Perez, Lizeth Joseline Fuentes
AU - Calla, Luciano Arnaldo Romero
AU - Valente, Luis
AU - Montenegro, Anselmo Antunes
AU - Clua, Esteban Walter Gonzalez
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/15
Y1 - 2016/12/15
N2 - Players may cease from playing a chosen gamesooner than expected for many reasons. One of the mostimportant is related to the way game designers and developerscalibrate game challenge levels. In practice, players havedifferent skill levels and may find usual predetermined difficultlevels as too easy or too hard, becoming frustrated or bored. The result may be decreased motivation to keep on playingthe game, which means reduced engagement. An approachto mitigate this issue is dynamic game difficulty balancing(DGB), which is a process that adjusts gameplay parametersin real-time according to the current player skill level. Inthis paper we propose a real-time solution to DGB usingEvolutionary Fuzzy Cognitive Maps, for dynamically balancinga game difficulty, helping to provide a well balanced level ofchallenge to the player. Evolutionary Fuzzy Cognitive Maps arebased on concepts that represent context game variables andare related by fuzzy and probabilistic causal relationships thatcan be updated in real time. We discuss several simulationexperiments that use our solution in a runner type game tocreate more engaging and dynamic game experiences.
AB - Players may cease from playing a chosen gamesooner than expected for many reasons. One of the mostimportant is related to the way game designers and developerscalibrate game challenge levels. In practice, players havedifferent skill levels and may find usual predetermined difficultlevels as too easy or too hard, becoming frustrated or bored. The result may be decreased motivation to keep on playingthe game, which means reduced engagement. An approachto mitigate this issue is dynamic game difficulty balancing(DGB), which is a process that adjusts gameplay parametersin real-time according to the current player skill level. Inthis paper we propose a real-time solution to DGB usingEvolutionary Fuzzy Cognitive Maps, for dynamically balancinga game difficulty, helping to provide a well balanced level ofchallenge to the player. Evolutionary Fuzzy Cognitive Maps arebased on concepts that represent context game variables andare related by fuzzy and probabilistic causal relationships thatcan be updated in real time. We discuss several simulationexperiments that use our solution in a runner type game tocreate more engaging and dynamic game experiences.
KW - Dynamic Game Difficulty Balancing
KW - Evolutionary Fuzzy Cognitive Maps
KW - Real-time Strategy
UR - https://www.scopus.com/pages/publications/85010289485
U2 - 10.1109/SBGames.2015.17
DO - 10.1109/SBGames.2015.17
M3 - Conference contribution
AN - SCOPUS:85010289485
T3 - Brazilian Symposium on Games and Digital Entertainment, SBGAMES
SP - 24
EP - 32
BT - Proceedings - 14th Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2015
A2 - de Carvalho, Flavia Garcia
A2 - de Vasconcellos, Marcelo Simao
A2 - Rodrigues, Maria Andreia Formico
PB - IEEE Computer Society
T2 - 14th Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2015
Y2 - 11 November 2015 through 13 November 2015
ER -