A three-mechanism symbolic learner reaches under 10 percent error in about 20 problems on two arithmetic tutor tasks, versus thousands for reinforcement learning and 2,000 to 8,000 for a single decision tree.
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Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency
A three-mechanism symbolic learner reaches under 10 percent error in about 20 problems on two arithmetic tutor tasks, versus thousands for reinforcement learning and 2,000 to 8,000 for a single decision tree.