在人类中同时学习随机性和挥发性的计算过程
Payam Piray1, Nathaniel D Daw2
1Department of Psychology, University of Southern California, Los Angeles, CA, USA. piray@usc.edu.
Nature communications
|October 21, 2024
概括
人类可以区分波动性和随机性,这两种环境噪声影响预测. 这种能力对于在不确定的条件下进行适应性决策和学习至关重要.
科学领域:
- 认知科学是一种认知科学.
- 计算神经科学是一种计算神经科学.
- 在不确定性下做决定
背景情况:
- 适应性决策依赖于结果预测,需要适应环境不确定性.
- 由于共享差异,在计算上区分波动性 (潜原因噪声) 和随机性 (观测噪声) 具有挑战性.
研究的目的:
- 为了调查人类是否可以将波动性和随机性放在一起时分离.
- 了解人类学习中这种分离背后的计算机制.
主要方法:
- 两个大规模的行为实验采用预测任务.
- 计算建模分析观察到的学习率和噪声参数.
主要成果:
- 人类表现出能够分离波动和随机性的能力,仅基于观测数据.
- 观察到的学习率显示了对波动性和随机性有截然不同的反应,与统计预测保持一致.
结论:
- 人类的认知可以区分不同的环境噪音来源.
- 结果支持计算模型,平衡竞争的波动性和随机性信号,用于适应性学习.
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