Reinforcement Learning Strategies for Pecs Card Selection in Augmentative and Alternative Communication Systems

Abstract

Autism spectrum disorder affects communication abilities, making augmentative and alternative communication systems essential for nonverbal individuals. The Picture Exchange Communication System is a structured, symbol-based method that enables nonverbal individuals to initiate communication by exchanging picture cards representing desired objects, actions, or concepts. It is widely used but requires efficient card selection strategies to maximize successful exchanges. This research evaluates the effectiveness of reinforcement learning algorithms combined with different card selection strategies. The experiments revealed that introducing opposite card selection after rejection significantly improved success rate compared to similarity-only approaches. The findings demonstrate that strategy design has greater impact on system performance than the choice of learning algorithm.