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A Review of Computational Classical Conditioning Models
Current Issue
Volume 2, 2015
Issue 2 (April)
Pages: 33-40   |   Vol. 2, No. 2, April 2015   |   Follow on         
Paper in PDF Downloads: 40   Since Aug. 28, 2015 Views: 1846   Since Aug. 28, 2015
Authors
[1]
Mehmet Emin Tagluk, Department of Electrical and Electronic Engineering, Inonu University, Malatya, Turkey.
[2]
Omer Faruk Ertugrul, Department of Electrical and Electronic Engineering, Batman University, Batman, Turkey.
Abstract
Classical conditioning (CC), which is a basic learning phenomenon, used to explain basic emotions, such as fear, phobia, and reflexes. It was introduced by Pavlov in 1927, and since then it has been investigated in psychological, behavioral, memory, neuroscience, and neurobiology perspectives. It has been used for investigating consumer behavior, conditional fear acquisition and extinction, response extinction and robotic control. Additionally, a large number of methods were proposed to model the CC learning stage. Unfortunately, none of them could model all outcomes of CC. In this study, these computational models, their usages and also the papers about their comparisons are reviewed. It obvious from this review that there is a high requirement to a model, which has a capability to model each feature of CC.
Keywords
Classical Conditioning, Pavlov, Computational Model, Behavioral Learning
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