Simulating symbolic distance e!ects in the transitive inference problem

The hippocampus is needed to store memories that are recon"gurable. Therefore, a hip-pocampal-like computational model should be able to solve transitive inference (TI) problems. By turning TI into a problem of sequence learning (stimuli-decisions-outcome), a sequence learning, hippocampal-like neural network solves the TI problem. In the transitive inference problem studied here, a network simulation begins by learning six pairwise relationships