Dynamic Difficulty Adjustment in a Whac-a-Mole like Game

Based on the Evolutionary Algorithm (EA) proposed by [1], this paper presents a new EA version with dynamic difficulty adjustment for a Whac-a-Mole like game used in motor rehabilitation of hand. This new version considers user performance as input and generates the position and time that the target will stay on screen. In order to simulate different users needs, a variety of player profiles were created with diverse horizontal movement speed (ulnar deviation/radial deviation of the hand) and vertical movement speed (supination/pronation of hand), as well as distinctive player attention deficits (response time to the apparition of the targets). The results show that the developed EA can adjust the difficulty factors of the game according to the skill set of each profile.