期刊
PSYCHONOMIC BULLETIN & REVIEW
卷 24, 期 2, 页码 557-565出版社
SPRINGER
DOI: 10.3758/s13423-016-1110-x
关键词
Bayesian modeling; Animal and human associative learning
资金
- Center for Brains, Minds and Machines (CBMM) - NSF STC [CCF-1231216]
The notion of context has played an important but complicated role in animal learning theory. Some studies have found that contextual stimuli (e.g., conditioning chamber) act much like punctate stimuli, entering into competition with other cues as would be predicted by standard associative learning theories. Other studies have found that contextual stimuli act more like occasion setters, modulating the associative strength of punctate stimuli without themselves acquiring associative strength. Yet other studies have found that context is often largely ignored, resulting in transfer of performance across context changes. This article argues that these diverse functions of context arise in part from different causal interpretations of the environment. A Bayesian theory is presented that infers which causal interpretation best explains an animal's training history, and hence which function of context is appropriate. The theory coherently accounts for a number of disparate experimental results, and quantitatively predicts the results of a new experiment designed to directly test the theory.
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