An elemental model of associative learning: I. Latent inhibition and perceptual learning

摘要: This paper presents a brief, informal outline followed by formal statement of an elemental associative learning model first described McLaren, Kaye, and Mackintosh (1989). The assumes representation stimuli sets elements (i.e., microfeatures) set algorithms that incorporate the following: real-time simulation learning; error-correcting rule; weight decay distinguishes between transient permanent associations; modulation gives high salience to and, hence, promotes rapid with novel, unpredicted reduces for stimulus as its error term declines. is applied in fashion some basic phenomena simple conditioning greater detail, latent inhibition perceptual learning. A detailed account generalization discrimination will be provided later paper.