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在不确定的世界中学习与选择:对静态和动态环境中探索-利用困境的研究。

Learning and choosing in an uncertain world: An investigation of the explore-exploit dilemma in static and dynamic environments.

作者信息

Navarro Daniel J, Newell Ben R, Schulze Christin

机构信息

School of Psychology, University of Adelaide, Australia.

School of Psychology, University of New South Wales, Australia.

出版信息

Cogn Psychol. 2016 Mar;85:43-77. doi: 10.1016/j.cogpsych.2016.01.001. Epub 2016 Jan 21.

Abstract

How do people solve the explore-exploit trade-off in a changing environment? In this paper we present experimental evidence from an "observe or bet" task, in which people have to determine when to engage in information-seeking behavior and when to switch to reward-taking actions. In particular we focus on the comparison between people's behavior in a changing environment and their behavior in an unchanging one. Our experimental work is motivated by rational analysis of the problem that makes strong predictions about information search and reward seeking in static and changeable environments. Our results show a striking agreement between human behavior and the optimal policy, but also highlight a number of systematic differences. In particular, we find that while people often employ suboptimal strategies the first time they encounter the learning problem, most people are able to approximate the correct strategy after minimal experience. In order to describe both the manner in which people's choices are similar to but slightly different from an optimal standard, we introduce four process models for the observe or bet task and evaluate them as potential theories of human behavior.

摘要

人们如何在不断变化的环境中解决探索与利用之间的权衡问题?在本文中,我们展示了来自一项“观察或下注”任务的实验证据,在该任务中,人们必须决定何时进行信息寻求行为,以及何时转向获取奖励的行动。特别地,我们专注于比较人们在变化环境中的行为与在不变环境中的行为。我们的实验工作是由对该问题的理性分析推动的,这种分析对静态和可变环境中的信息搜索和奖励寻求做出了强有力的预测。我们的结果表明人类行为与最优策略之间存在惊人的一致性,但也突出了一些系统性差异。特别地,我们发现虽然人们在首次遇到学习问题时经常采用次优策略,但大多数人在经过最少的经验后能够接近正确策略。为了描述人们的选择与最优标准相似但又略有不同的方式,我们为“观察或下注”任务引入了四个过程模型,并将它们作为人类行为的潜在理论进行评估。

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