A response function that maps associative strengths to probabilities.

IF 1.2 4区 心理学 Q4 BEHAVIORAL SCIENCES
Stefano Ghirlanda
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引用次数: 1

Abstract

Bridging associative and normative theories of animal learning, I show that an associative system can behave as if performing probabilistic inference by using the function f(V) = 1 - e-cV to transform associative strengths (V) into response probabilities. For example, using this function, an associative system can respond normatively to a compound stimulus AB, given previous separate experiences with the components A and B. The CR probability formulae that result from the proposed function have a normative interpretation in terms of statistical decision theory. The formulae also suggest a normative interpretation of stimulus generalization as a heuristic to infer whether different stimuli are likely to convey redundant or independent information about reinforcement. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

将联想强度映射到概率的响应函数。
通过连接动物学习的关联理论和规范理论,我展示了一个关联系统可以表现得就像通过使用函数f(V) = 1 - e-cV将关联强度(V)转换为响应概率来进行概率推理一样。例如,使用这个函数,一个关联系统可以对复合刺激AB做出规范的响应,给定之前对组件a和b的单独经验。从所提出的函数中得出的CR概率公式在统计决策理论方面具有规范的解释。该公式还提出了刺激泛化的规范解释,作为一种启发式方法来推断不同的刺激是否可能传达有关强化的冗余或独立信息。(PsycInfo Database Record (c) 2022 APA,版权所有)。
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来源期刊
Journal of Experimental Psychology-Animal Learning and Cognition
Journal of Experimental Psychology-Animal Learning and Cognition Psychology-Experimental and Cognitive Psychology
CiteScore
2.90
自引率
23.10%
发文量
39
期刊介绍: The Journal of Experimental Psychology: Animal Learning and Cognition publishes experimental and theoretical studies concerning all aspects of animal behavior processes.
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