English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Various types of discrimination learning tasks, such as so-called nonconditional, conditional, and biconditional tasks, are generally held to differ in complexity and to require different amounts of training. However, rather than a difference in rule complexity, between-task performance differences may reflect a difference in number of underlying rules. Accordingly, in the present study, human participants were subjected to tasks differing in number and/or complexity of rules. In Experiments 1 and 3, participants learned to differentially respond to visual-target stimuli, each of which was preceded by a visual feature. Conditions differed in the number of different features and in the informational value of individual features and/or targets. In Experiment 2, participants were fully informed about all relevant stimulus-response mappings prior to each trial. Performance accuracy was primarily determined by number of underlying rules in the initial phase of discrimination learning, especially when the time available for responding was restricted. However, when participants had attained a high accuracy level, performance was solely determined by rule complexity. Apparently, number and complexity of rules have a different weight, depending on the stage of discrimination learning.

Discrimination learning in humans: Role of number and complexity of rules