Bayesian theories of conditioning in a changing world
Bayesian theories of conditioning in a changing world
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DOI：
10.1016/j.tics.2006.05.004
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发表时间：
2006-07-01
影响因子：
19.9
通讯作者：
Touretzky, David S.
中科院分区：
文献类型：
--
作者：
Courville, Aaron C.;Daw, Nathaniel D.;Touretzky, David S.
贝叶斯方法最近的蓬勃发展促使人们重新审视行为中的经典问题，甚至在巴甫洛夫条件反射这样古老的领域也是如此。统计数据可以为行为提供一种新的、原则性的解释，以前的实验和理论可以为贝叶斯企业的许多未被探索的方面提供信息。在这里，我们考虑一个这样的问题：发现令人惊讶的事件会促使动物学习得更快。我们认为，在对条件反射的统计描述中，意外信号会发生变化，因此不确定性和新学习的必要性。我们讨论了在一个不断变化的世界中的推理，并展示了如何从这个角度解释涉及惊喜的实验结果，以及如何因此理解这些现象有助于约束动物和人类学习的统计理论。
The recent flowering of Bayesian approaches invites the re-examination of classic issues in behavior, even in areas as venerable as Pavlovian conditioning. A statistical account can offer a new, principled interpretation of behavior, and previous experiments and theories can inform many unexplored aspects of the Bayesian enterprise. Here we consider one such issue: the finding that surprising events provoke animals to learn faster. We suggest that, in a statistical account of conditioning, surprise signals change and therefore uncertainty and the need for new learning. We discuss inference in a world that changes and show how experimental results involving surprise can be interpreted from this perspective, and also how, thus understood, these phenomena help constrain statistical theories of animal and human learning.