Abstract

•Relational reasoning underlies a myriad uniquely human abilities. •Multiple cognitive and neural systems underlie abilities to perceive and reason about relations. •Human alone possess a Late System for reasoning, based on a frontoparietal neural network. •Computational models in cognitive science and machine learning are addressing relation learning. We review recent theoretical and empirical work on the emergence of relational reasoning, drawing connections among the fields of comparative psychology, developmental psychology, cognitive neuroscience, cognitive science, and machine learning. Relational learning appears to involve multiple systems: a suite of Early Systems that are available to human infants and are shared to some extent with nonhuman animals; and a Late System that emerges in humans only, at approximately age three years. The Late System supports reasoning with explicit role-governed relations, and is closely tied to the functions of a frontoparietal network in the human brain. Recent work in cognitive science and machine learning suggests that humans (and perhaps machines) may acquire abstract relations from nonrelational inputs by means of processes that enable re-representation.

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