Using Games to Study Law of Motions in Mind

Abstract

The development of games had been seen as an essential field of study in artificial intelligence. Although game concepts have been adopted in various problem domains, understanding the nature of game playing's underlying mechanism has been limited. This study investigates such a mechanism by adopting a logistic model of game outcome uncertainty where a measure of game refinement had been derived. Application of such a measure to the popular board and sports games have been conducted to determine its implication in determining sophisticated design and has defined the harmonic balance between skill and chance. A theoretical analysis using practical data confirms the effectiveness of the proposed model, where reasonable game length is determined based on the definition of a gamified experience. The model is further expanded with the analogy of physics in mind. The law of motions in the game is formalized by considering the derivatives of the game progress model, where the link between game refinement theory and flow theory is identified and discussed. In essence, the sophisticated game's underlying mechanism leads to a more natural yet pleasurable human experience.