Learning sets of causally related concepts

Researchers debate whether higher-order learning can be reduced to an associative process. To shed light on this question, we perform two psychological experiments - the results of which cannot be accounted for by any current model of concept acquisition learning. We investigate inducing a set of causally related conceptsfrom examples. We show that human subjects make fewer errors and leam more rapidly when the set of concepts is logically consistent - whether the concepts are learned sequentially or simultaneously. We compare the results of these subjects to subjects learning equivalent concepts that share sets of relevant features, but are not logically consistent. We enhance a neural network model to simulate our psychological experiments