谷歌浏览器插件
订阅小程序
在清言上使用

Regret in Experience-Based Decisions: the Effects of Expected Value Differences and Mixed Gains and Losses.

Decision(2021)

引用 5|浏览3
暂无评分
摘要
Previous research on experience-based decisions with complete feedback supports the idea that people generally prefer options that produce better outcomes most of the time. The current study explored whether this preference is modulated by differences in expected value (EV) and the presence or absence of occasional losses. Participants (n = 52) recruited through a crowdsourcing platform completed an online experiment that involved repeated choices between a safer and a riskier option while receiving complete feedback. The riskier option yielded a better outcome on 80% of draws so that choosing it minimized the probability of regret. Preference for the riskier option was high when it had the same EV as the safer option and all outcomes were gains, but it decreased when the safer option had a higher EV and when both options included occasional losses. These findings replicated the results of a preliminary experiment with undergraduate participants (n = 105). Outcome ratings obtained on 50% of trials showed large effects of regret and rejoicing, confirming that participants were sensitive to relative comparisons between obtained and forgone outcomes. Reinforcement-learning modeling indicated that the effects of unequal EVs and mixed outcomes could be accounted for by assuming combined encoding of absolute and relative outcomes and unequal weighting of gains and losses. Overall, our results suggest that minimizing the probability of regret is an important motivational factor in experience-based decisions, but structural features of the choice environment can modulate the extent to which decision makers follow this strategy.
更多
查看译文
关键词
reinforcement-learning models,complete feedback,regret theory,relative valuation,loss aversion
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要