Designing a Serious Game for Children with Autism using Reinforcement Learning and Fuzzy Logic

Autism spectrum disorder (ASD) is a collection of inconstant characteristics. Anomalies in reciprocal social communications and disabilities in perceiving communication patterns characterize These features. Also, exclusive repeated interests and actions identify ASD. Computer games have affirmative effects on autistic children. Serious games have been widely used to elevate the ability to communicate with other individuals in these children. In this paper, we propose an adaptive serious game to rate the social skills of autistic children. The proposed serious game employs a reinforcement learning mechanism to learn such ratings adaptively for the players. It uses fuzzy logic to estimate the communication skills of autistic children. The game adapts itself to the level of the child with autism. For that matter, it uses an intelligent agent to tune the challenges through playtime. To dynamically evaluate the communication skills of these children, the game challenges may grow harder based on the development of a child's skills through playtime. We also employ fuzzy logic to estimate the playing abilities of the player periodically. Fifteen autistic children participated in experiments to evaluate the presented serious game. The experimental results show that the proposed method is effective in the communication skill of autistic children.