Modification of Game Agent Using Genetic Algorithms in Game Card Battle Nathanael Aldo Phillip (a*), Silvester Dian Handy Permana (a), Maya Cendana (b)
a) Program Studi Teknik Informatika, Universitas Trilogi
Jl. TMP Kalibata No. 1, Jakarta 12760, Indonesia.
*nathanaelphillip[at]trilogi.ac.id
b) Program Studi Teknik Informatika, Universitas Bunda Maria
Jl. Lodan Raya No.2, Jakarta 14430, Indonesia.
Abstract
Game Agent is currently being developed to be an opponent in games, including games with the Card genre. Game Agents in traditional Card Games - such as poker, domino, or mahjong cards - have abilities that depend on the value of the cards, but the ability of these Game Agents will not be optimal if used in the Card Battle game. This is because Card Battle has many attributes that have to be processed to become an opponent. Therefore, this research modifies the Game Agent with Genetic Algorithms to optimize the playing ability of the Game Agent in Card Battle. The computational stages and fitness formula of the Genetic Algorithm are adjusted to the Card Battle rules to increase the computational speed of the Genetic Algorithm. The results of this study prove that Game Agent modification using Genetic Algorithm provides a more optimal playing ability than its predecessor algorithm. Game Agent that has been modified has several abilities that are not owned by the previous Game Agent, such as playing cards to attack the opponent directly and storing SP (Summon Points) they have
