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Enhancing metacognitive reinforcement learningusing reward structures and feedback
Abstract
How do we learn to think better, and what can we do to pro-mote such metacognitive learning? Here, we propose that cog-nitive growth proceeds through metacognitive reinforcementlearning. We apply this theory to model how people learn howfar to plan ahead and test its predictions about the speed ofmetacognitive learning in two experiments. In the first experi-ment, we find that our model can discern a reward structure thatpromotes metacognitive reinforcement learning from one thathinders it. In the second experiment, we show that our modelcan be used to design a feedback mechanism that enhancesmetacognitive reinforcement learning in an environment thathinders learning. Our results suggest that modeling metacog-nitive learning is a promising step towards promoting cognitivegrowth.
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