Adaptive Scenario Selection in Serious Games Using Finite State Machines and Agent-Based Models
Melissa Rêgo Rodrigues
This study presents a hybrid approach to scenario adaptation in serious games, using Finite State Machines (FSMs) and Agent-Based Models (ABMs). Focusing on the educational RPG genre of software development, the proposed model aims to automatically adjust the behavior of non-playable characters (NPCs) and the game's progression based on the player's actions and preferences. The methodology included a literature review, followed by the development of a simulation in the JFLAP software, integratin