新性作为人类在复杂的随机环境中探索的驱动力
Alireza Modirshanechi1,2,3,4, Wei-Hsiang Lin1, He A Xu1
1School of Life Sciences, Brain-Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland.
概括
人类探索随机环境以获得奖励,以新为指导. 这项研究揭示了以新驱动的探索,而不仅仅是信息获取,在复杂的,无奖励的环境中影响人类的决策.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 人工智能的人工智能
背景情况:
- 人类对奖励的探索往往涉及到在没有立即回报的情况下导航环境.
- 假设内在的奖励,如新性,惊喜或信息获取,驱动了这种探索.
- 基于内在的奖励信号,人工智能对随机性有不同的反应,其中一些易受"噪音电视问题"的影响.
研究的目的:
- 为了调查人类是否被无奖励的随机性所吸引,类似于人工制剂.
- 确定驱动人类在具有随机元素的复杂环境中的探索的主要内在奖励信号.
主要方法:
- 设计了一项多步决策任务,以模拟复杂的环境.
- 参与者在一个具有高随机性但没有外部奖励的区域内寻找奖励状态.
- 计算建模比较了以新驱动,以信息获取驱动和以惊喜驱动的探索策略.
主要成果:
- 参与者一直在探索随机的,没有奖励的子区域.
- 在这个范式中,人类的决策最好通过一种以新驱动的探索策略来解释.
- 新奇驱动的探索比基于信息获取或惊喜的策略更适合.
结论:
- 人类在复杂环境中的探索受到外部奖励和内在新奇性的影响.
- 新性在引导探索方面发挥着重要作用,即使存在随机,无奖励的刺激.
- 这些发现表明人类探索的双重控制机制:外部奖励和内在的新性.
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