Reinforcement, Rationality, and Intentions: How Robust Is Automatic Reinforcement Learning in Economic Decision Making?

Reinforcement, Rationality, and Intentions: How Robust Is Automatic Reinforcement Learning in Economic Decision Making?
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强化、理性和意图:自动强化学习在经济决策中的鲁棒性如何?

DOI:
10.1002/bdm.2008
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发表时间:
2017
影响因子:
2
通讯作者:
Achtziger
Achtziger
中科院分区:
心理学3区
文献类型:
--
作者:
Hügelschäfer;Achtziger

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强化学习在经济决策中经常被观察到,并可能导致有害的决策。由于它的自动性,它很难避免。在三个实验研究中,我们考察了这一过程是否可以受到目标意图和实施意图的控制。在概率更新任务中考察了参与者的决策,其中最大化预期收益的规范规则(贝叶斯规则)与作为简单决策规则的强化启发式规则相冲突。一些参与者被要求设定目标意图,以促进理性决策的优化,而另一些参与者被要求提供这些目标意图和实施意图。结果表明,通过目标意图或实施意图来控制强化学习的自动过程是可能的,这些意图将决策者的注意力集中在决策反馈的分析上。重要的是,这样的有益效果并不是通过简单地指示参与者分析反馈而实现的,而没有从第一人称的角度将目标定义为期望的最终状态。对于旨在通过控制负面情绪来关闭强化过程的意图,效果更为复杂,并取决于特定的目标导向行为。抑制负反馈引起的失望情绪的目标意图在控制强化过程中效果不佳。为这一目标提供执行意图甚至产生了事与愿违的结果,加强了不必要的加固进程。相比之下,要求参与者通过使用目标意图或实施意图来应对负面决策结果时保持冷静,会增加符合贝叶斯规则的决策。版权所有©2017 John Wiley&Sons,Ltd.
Reinforcement learning is often observed in economic decision making and may lead to detrimental decisions. Because of its automaticity, it is difficult to avoid. In three experimental studies, we investigated whether this process could be controlled by goal intentions and implementation intentions. Participants' decisions were investigated in a probability‐updating task in which the normative rule to maximize expected payoff (Bayes' rule) conflicted with the reinforcement heuristic as a simple decision rule. Some participants were asked to set goal intentions designated to foster the optimization of rational decision making, while other participants were asked to furnish these goal intentions with implementation intentions. Results showed that controlling automatic processes of reinforcement learning is possible by means of goal intentions or implementation intentions that focus decision makers on the analysis of decision feedback. Importantly, such beneficial effects were not achieved by simply instructing participants to analyze the feedback, without defining a goal as the desired end state from a first‐person perspective. Regarding intentions supposed to shut down reinforcement processes by controlling negative affect, effects were more complex and depended on the specified goal‐directed behavior. The goal intention to suppress the disappointment elicited by negative feedback was not effective in controlling reinforcement processes. Furnishing this goal with an implementation intention even backfired and strengthened unwanted reinforcement processes. In contrast, asking participants to keep cool in response to negative decision outcomes through the use of goal intentions or implementation intentions increased decisions in line with Bayes' rule. Copyright © 2017 John Wiley & Sons, Ltd.
DOI: 10.1016/j.brainres.2016.08.026
发表时间: 2016-10
期刊: Brain Research
影响因子: 2.9
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