Exploring Natural Language-Based Strategies for Efficient Number Learning in Children through Reinforcement Learning

ArXi:2410.08334v2 Announce Type: replace-cross In this paper, we build a reinforcement learning framework to study how children compose numbers using base-ten blocks. Studying numerical cognition in toddlers offers a powerful window into the learning process itself, because numbers sit at the intersection of language, logic, perception, and culture. Specifically, we utilize state of the art (SOTA) reinforcement learning algorithms and neural network architectures to understand how variations in linguistic instructions can affect the learning process.