Learning to Reach by Constraining the Movement Search Space

Trial‐and‐error learning strategies play a central role in sensorimotor development during early infancy. However, learning to reach by trial‐and‐error normally requires a slow and laborious search through the space of possible movements. We propose a computational model of reaching based on the notion that early sensorimotor control is driven by the generation of exploratory movements, followed by the selection and maintenance of adaptive movement patterns. We find that, instead of exhaustively exploring the full search space of movement patterns, the model exploits several emergent constraints that limit the initial size of the movement search space. These constraints exploit both mechanical and kinematic properties of the reaching task. We relate these results to the development of reaching during infancy, and discuss recent findings that have identified similar constraints in young infants.