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?
复制标题
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
复制
发表时间:
2017
影响因子:
2
通讯作者:
Achtziger
中科院分区:
文献类型:
--
作者:
Hügelschäfer;Achtziger
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.
登录
查看更多内容
影响因子:
2.9
作者:
Sabine Hügelschäfer;Alexander Jaudas;A. Achtziger
通讯作者:
Sabine Hügelschäfer;Alexander Jaudas;A. Achtziger
影响因子:
1.8
作者:
Suchodoletz;Achtziger
通讯作者:
Achtziger
影响因子:
3.8
作者:
Alós-Ferrer C;Hügelschäfer S;Li J
通讯作者:
Li J
DOI:
--
发表时间:
--
期刊:
影响因子:
--
作者:
A. Achtziger;P. Gollwitzer;P. Sheeran
通讯作者:
P. Sheeran
影响因子:
3.9
作者:
BAUMEISTER, RF;SHOWERS, CJ
通讯作者:
SHOWERS, CJ