Meningkatkan Variasi Tindakan Non-Playable Character Pada Game Survival Menggunakan Metode Markov - Hendra Winata; Liliana Liliana; Hans Juwiantho (Jurnal Infra, 2021)
Digital games or often called Video games are common today. The development of game variants makes games never stop improving, especially in the Artificial Intelligence section. Each game has its own artificial intelligence so that many variations are generated and make a game unique. This research tries to make a variation of the actions taken by NPCs against players. In an effort to make these variations, the Markov Chain method is used to help state selection. Markov Chain method is combined with Finite-State Machine for NPC state selection. Based on the results of testing and questionnaires, 80.4% strongly agree and 19.6% agree that the resulting NPC has a large variety of actions. The results of the questionnaire also found that 69.6% were very unrealistic and 30.4% said that NPCs were unrealistic or did not imitate human behavior.