Generalization guides human exploration in vast decision spaces

Generalization guides human exploration in vast decision spaces
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泛化指导人类在广阔的决策空间中进行探索

DOI:
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发表时间:
2017
影响因子:
29.9
通讯作者:
Björn Meder
Björn Meder
中科院分区:
心理学1区
文献类型:
--
作者:
Charley M. Wu;Eric Schulz;M. Speekenbrink;Jonathan D. Nelson;Björn Meder

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从觅食到学习复杂的游戏,人类行为的许多方面都可以被视为一个搜索问题,具有广阔的可能行动空间。在有限的搜索范围内,最优解通常是无法获得的。然而,人类如何驾驭巨大的问题空间,这需要对未观察到的行为进行智能探索?使用各种强盗任务与多达121个武器,我们研究人类如何在有限的搜索范围内搜索奖励,其中奖励的空间相关性(在生成和自然环境中)提供牵引力的推广。在各种不同的概率和启发式模型中,我们发现高斯过程函数学习与乐观的置信上限采样策略相结合的证据,提供了人们如何使用泛化来指导搜索的强大解释。我们的建模结果和参数估计是可恢复的,可用于模拟类似人类的性能,提供有关复杂环境中人类行为的见解。在复杂、陌生的环境中寻找奖励时,通常不可能探索所有选项。Wu等人展示了泛化和乐观采样的结合如何指导人类在复杂环境中的有效探索。
From foraging for food to learning complex games, many aspects of human behaviour can be framed as a search problem with a vast space of possible actions. Under finite search horizons, optimal solutions are generally unobtainable. Yet, how do humans navigate vast problem spaces, which require intelligent exploration of unobserved actions? Using various bandit tasks with up to 121 arms, we study how humans search for rewards under limited search horizons, in which the spatial correlation of rewards (in both generated and natural environments) provides traction for generalization. Across various different probabilistic and heuristic models, we find evidence that Gaussian process function learning—combined with an optimistic upper confidence bound sampling strategy—provides a robust account of how people use generalization to guide search. Our modelling results and parameter estimates are recoverable and can be used to simulate human-like performance, providing insights about human behaviour in complex environments. When searching for rewards in complex, unfamiliar environments, it is often impossible to explore all options. Wu et al. show how a combination of generalization and optimistic sampling guides efficient human exploration in complex environments.
人类使用定向和随机探索来解决探索-利用困境。
DOI: 10.1037/a0038199
发表时间: 2014
期刊: Journal of experimental psychology. General
影响因子: --
作者:
Wilson,RobertC;Geana,Andra;White,JohnM;Ludvig,ElliotA;Cohen,JonathanD
通讯作者: Cohen,JonathanD