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基于时间的奖励最大化。

Time-based reward maximization.

机构信息

Department of Psychology, Koç University, , Istanbul, Turkey.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2014 Jan 20;369(1637):20120461. doi: 10.1098/rstb.2012.0461. Print 2014 Mar 5.

Abstract

Humans and animals time intervals from seconds to minutes with high accuracy but limited precision. Consequently, time-based decisions are inevitably subjected to our endogenous timing uncertainty, and thus require temporal risk assessment. In this study, we tested temporal risk assessment ability of humans when participants had to withhold each subsequent response for a minimum duration to earn reward and each response reset the trial time. Premature responses were not penalized in Experiment 1 but were penalized in Experiment 2. Participants tried to maximize reward within a fixed session time (over eight sessions) by pressing a key. No instructions were provided regarding the task rules/parameters. We evaluated empirical performance within the framework of optimality that was based on the level of endogenous timing uncertainty and the payoff structure. Participants nearly tracked the optimal target inter-response times (IRTs) that changed as a function of the level of timing uncertainty and maximized the reward rate in both experiments. Acquisition of optimal target IRT was rapid and abrupt without any further improvement or worsening. These results constitute an example of optimal temporal risk assessment performance in a task that required finding the optimal trade-off between the 'speed' (timing) and 'accuracy' (reward probability) of timed responses for reward maximization.

摘要

人类和动物可以高精度地(但精度有限地)判断几秒钟到几分钟之间的时间间隔。因此,基于时间的决策不可避免地受到我们内源性定时不确定性的影响,因此需要进行时间风险评估。在这项研究中,当参与者必须将每个后续反应的最小持续时间延迟以赚取奖励,并且每个反应都会重置试验时间时,我们测试了人类的时间风险评估能力。在实验 1 中,过早的反应不会受到惩罚,但在实验 2 中会受到惩罚。参与者通过按键在固定的会话时间内(超过八次会话)尝试最大化奖励。没有关于任务规则/参数的说明。我们在基于内源性定时不确定性水平和收益结构的最优性框架内评估了经验性能。参与者在两个实验中都几乎跟踪了最优的目标反应间时间(IRT),该时间随着定时不确定性水平的变化而变化,并最大化了奖励率。对最优目标 IRT 的获取是迅速而突然的,没有任何进一步的改进或恶化。这些结果构成了在需要为奖励最大化找到定时反应的“速度”(定时)和“准确性”(奖励概率)之间的最佳权衡的任务中进行最优时间风险评估性能的一个例子。

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