Fuzzy Markov Process for Determining the Rarity of Rewards in Rooms in Roguelike Games

Roguelike games are known for their procedurally generated environments, offering a unique gameplay experience with each playthrough. One crucial aspect of these games is the distribution of rewards within the game’s rooms. The rarity of rewards can greatly impact player engagement and satisfaction. Fuzzy Markov Processes (FMP) provide a flexible framework for capturing uncertainty and randomness in sequential decision-making problems. By incorporating fuzziness into the Markov process, our approach allows for a smooth transition between reward rarity states, enabling a more nuanced and dynamic gameplay experience. The fuzzy nature of the model permits rewards to have varying degrees of rarity, enhancing the sense of discovery and unpredictability for players. By leveraging FMPs, developers can create intricate reward distributions that adapt to player behaviour and preferences, resulting in a more personalized and engaging gameplay experience. The main objective of this research is to propose a novel framework that utilizes a fuzzy Markov process to effectively model and analyse the rarity of rewards in these rooms.