A Simulator for Analyzing the Balance of Mafia Game

• Published in: 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) pp. 622 - 627
• Main Author: Chang, Qiong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2020
• Subjects: Conferences; Entertainment industry; Game Refinement Theory; Games; Mafia; Mathematical model; Real-time systems; Reliability theory; Simulator
• DOI: 10.1109/ICAIIS49377.2020.9194822

Mafia, a game with high logic, is very popular around the world. Players from all over the world constantly alter the rules of the game to increase the complexity and the entertainment of the game. With increasing the character and number of participants, the balance between the citizens and Mafias is more difficult to maintain. Although little study has been done on Mafia Game, there are some studies which indicate to us the criteria and methods to maintain balance. Among them, there are two main theories: 1) Some studies present the best ratio of the number of Citizens and Mafias, from the perspective of the winning-chance, and use a mathematical model to prove the correctness of the ratio for simple version. 2) Some studies focus on selecting the best ratio from the perspective of the entertainment by analyzing the overall death toll based on the Game Refinement Theory. Although the two above theories have different perspectives and their conclusions are not absolute, both of them are necessary for players. However, most of the studies only do their evaluation according to the theories of themselves, and few studies combine the two theories together to analysis the balance of the Mafia Game between the different characters. In this paper, we proposed simulator which can simulate the various of actions more realistically in Mafia Game. Different from other simulators, it adds a weight of credibility to each character, which can change continuously as the game progresses, and make it more clearly to distinguish the identity of each player. Additionally, the simulation results are analyzed according to the above two theories, which helps us to understand the relationship between the them, and to find a best combination solution dynamically as the change of the total number of players.