Modeling Acquisition of a Torque Rule on the Balance-scale Task

Abstract

We present a new model of development of children’s performance on the balance-scale task, one of the most common benchmarks for computational modeling of development. Knowledge-based cascade-correlation (KBCC) networks progress through all four stages seen in children, ending with a genuine torque rule that can solve problems only solvable by comparing torques. A key element in the model is injection of a neurally-implemented torque rule into the recruitment pool of KBCC networks, mimicking the explicit teaching of torque in secondary-school science classrooms.


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