Project Description: The project around an escape game scenario wherein a incarcerated individual must devise a strategy to evade pursuit by law enforcement. The core gameplay mechanics entail players deducing the optimal course of action for their escape. An erroneous decision by the player will result in apprehension by the pursuing police force, while a correct choice will propel the prisoner closer to their goal of freedom. To achieve this interactive experience, the project leverages ML techniques integrated within the Scratch 3.0 platform. This entails the use of algorithms and data-driven decision-making processes to enhance the realism and complexity. ML algorithms may be employed to simulate police behavior and adapt their pursuit strategies based on the player's decisions, thereby adding an additional layer of challenge and unpredictability to the gameplay. This project aims to provide players with a captivating and intellectually stimulating escape game experience while showcasing the potential of Machine Learning
