Unsupervised learning of complex associations in an animal model

Supervised learning results from explicit corrective feedback, whereas unsupervised learning results from statistical co-occurrence. In an initial training phase, we gave pigeons an unsupervised learning task to see if mere pairing could establish associations between multiple pairs of visual images. To assess learning, we administered occasional testing trials in which pigeons were shown an object and had to choose between previously paired and unpaired tokens. Learning was evidenced by preferential choice of the previously unpaired token. In a subsequent supervised training phase, learning was facilitated if the object and token had previously been paired. These results document unsupervised learning in pigeons and resemble statistical learning in infants, suggesting an important parallel between human and animal cognition.