论文标题
我做了足够的计划还是应该计划更多？
Have I done enough planning or should I plan more?
论文作者
论文摘要
人们关于如何分配有限的计算资源的决定对人类智能至关重要。这种元认知能力的重要组成部分是决定是否继续思考要做什么并继续下一个决定。在这里，我们表明人们通过学习和反向工程来获得这种能力，这些能力的基础学习机制。使用外部人类计划的过程追踪范式，我们发现人们很快就适应了他们执行的计划，以实现计划的成本和收益。为了发现潜在的元认知学习机制，我们以元认知特征和执行的贝叶斯模型选择增强了一组强化学习模型。我们的结果表明，可以通过元认知伪奖励指导的元认知能力来调整规划数量的能力，以传达计划的价值。
People's decisions about how to allocate their limited computational resources are essential to human intelligence. An important component of this metacognitive ability is deciding whether to continue thinking about what to do and move on to the next decision. Here, we show that people acquire this ability through learning and reverse-engineer the underlying learning mechanisms. Using a process-tracing paradigm that externalises human planning, we find that people quickly adapt how much planning they perform to the cost and benefit of planning. To discover the underlying metacognitive learning mechanisms we augmented a set of reinforcement learning models with metacognitive features and performed Bayesian model selection. Our results suggest that the metacognitive ability to adjust the amount of planning might be learned through a policy-gradient mechanism that is guided by metacognitive pseudo-rewards that communicate the value of planning.
