A computational game experience analysis via game refinement theory

From the perspective of audiences, game refinement (GR) theory is a theory and measurement that was frequently used to assess the enjoyment and complex features of games. We conjectured that when we play a strategy game, there is a physical information process in our minds which subject to Newton’s laws. It focuses on the uncertainty of game outcomes, where the game’s components were abstracted to produce the game information progression utilizing the game outcome (achievement or solved uncertainty) and game length (usually designed by total steps or moves). This quantification defines the measure of informational acceleration, in which thrills and excitement may be measured using Newton’s second law F=ma (Informational acceleration is correlated with force in mind). Changes in acceleration, on the other hand, would have an impact on game dynamics, particularly in hostile scenarios. The jerk value is used to correct the game dynamic by using a derivative of the acceleration readings. In the gaming setting, many physical factors linked to psychological feelings are explored. To illustrate the physical and psychological relationships, the game information progress is represented in our minds. By determining reasonable informational jerk values related to the game process’s success rate and informational acceleration, this development of game refinement theory provides a more player-driven experience.