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强化学习和奖励的积极性与厌恶的结果
Elizabeth A Bauer1, Brandon K Watanabe1, Annmarie MacNamara1
1Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA.
Psychophysiology
|November 23, 2023
概括
奖励积极性 (RewP) 组件,衡量奖励响应性,在冲击任务中没有显示出意外负面结果的增强信号. 这挑战了强化学习理论,建议奖励和期望的附加效应.
科学领域:
- 神经科学是一个神经科学.
- 认知心理学 认知心理学
- 计算神经科学是一种神经科学.
背景情况:
- 奖励积极性 (RewP) 是一个与事件相关的潜在 (ERP) 组件,反映了奖励响应性.
- 强化学习 (RL) 理论预测,对于意想不到的积极结果,RewP是最大的.
- 之前的研究表明,当将RL理论应用于厌恶结果时,特别是在被动任务中,结果各不相同.
研究的目的:
- 测试RL理论对RewP的预测,在一个积极的,基于选择的任务中使用厌恶结果.
- 调查RewP是否作为奖励信号,当奖励被定义为没有冲击时.
- 澄清奖励和预期之间的相互作用,以调整 RewP.
主要方法:
- 80名参与者完成了一项与操纵的冲击预期对冲击门的威胁任务.
- 主要组件分析被用来将RewP与其他ERP组件分开.
- 参与者看到了红色 (预期的冲击) 或绿色 (意想不到的冲击) 边框的门.
主要成果:
- 观察到 RewP 是一种奖励信号 (没有冲击 > 冲击).
- RewP没有被强化为意想不到的反,与RL理论预测相反.
- 对于意想不到的反而不是预期的反,RewP总体上更大,这表明了附加效应.
结论:
- RewP反映了奖励和期望的附加效应,而不是相互作用,挑战了RL理论.
- 这些发现表明RL理论可能无法完全解释RewP,当奖励是缺少厌恶结果时.
- 积极的任务参与和奖励的定义 (厌恶性与食欲性) 是RewP调节的关键因素.
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