Implementation of artificial intelligence with 3 different characters of AI player on “Monopoly Deal” computer game

Abstract

Monopoly Deal is a card game that derived directly from the traditional Monopoly Game. The game consists of a set of cards as a game device. This game aims to collect three different sets of property cards. This research has been conducted to explore the potential for further developing this simulation game, by implementing rules and strategies of Monopoly Deal. BFS method was used as the algorithm of the game. The character of players in the game is divided into three kinds, namely: Aggressive, Defensive, and Normal. Each character would make a different influence on the provision of assets and on the selection of card or money being played. The implementation of the game consists of characters, check assets system, and the computer-based card game itself with AI intelligence player. The testing results show that the combination of aggressive character and logical asset as the highest winning rate of 45%.