Fuzzy-based Dynamic Reward for Discovery Activity in Appreciative Serious Game

Abstract

Interactivity and experience as the main characteristics of serious game has made it considered one of the most promising learning tools. Those characteristics supported mainly by game activity. Therefore, activity design is one of the most important element in developing serious game. One of the activity design concepts is to use Appreciative Learning, which consists of the stages of Discovery, Dream, Design and Destiny. The activity of exploration in Discovery stage is the main activity which is dominated by search and exploration. Because it is a search and exploration activity, it takes a long time and contains uncertainty in achievement. Dynamic rewards are needed to support the continuity of this Discovery activity. A good reward keeps the player’s focus on searching and exploration by providing indicators of achievement. This study uses fuzzy logic to form dynamic reward behavior in Discovery activities. Fuzzy logic considered one of the artificial intelligence methods that is suitable for games because of lightweight computation and could produce expressive AI behavior. The criteria used as input are the percentage of exploration and time, which will generate dynamic rewards for Discovery activities. The results of this study, fuzzy logic can produce three levels of variance of reward.