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Common physical properties among relational networks improve analogy aptness
Author(s) -
Ruiz Francisco J.,
Luciano Carmen
Publication year - 2015
Publication title -
journal of the experimental analysis of behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.75
H-Index - 61
eISSN - 1938-3711
pISSN - 0022-5002
DOI - 10.1002/jeab.147
Subject(s) - analogy , node (physics) , equivalence relation , equivalence (formal languages) , computer science , test (biology) , psychology , artificial intelligence , mathematics , discrete mathematics , linguistics , paleontology , philosophy , structural engineering , engineering , biology
Relational frame theory (RFT) conceptualizes analogy as the establishment of a relation of coordination among common types of relations. This study provided an initial RFT analysis of analogy aptness. Twenty participants initially learned to respond to the structure of analogical tests after which they were trained on two separate relational networks, each consisting of three equivalence classes (Network: 1 F1‐G1‐H1, F2‐G2‐H2, F3‐G3‐H3; Network 2: M1‐N1‐O1, M2‐N2‐O2, M3‐N3‐O3). The node stimuli always appeared with color spots on their backgrounds (F1 and M1: yellow; F2 and M2: red; F3 and M3: blue). In the critical test, participants had to select the more correct response from two options: relating combinatorial relations of coordination with the same color in the node stimuli (e.g., relating G1H1 to N1O1) versus relating combinatorial relations with different colors in the node stimuli (e.g., relating G1H1 to N2O2). The colors of the node stimuli did not appear on the critical test. Ninety percent of participants selected the analogies with common color properties as the more correct ones. Practical implications of these findings are discussed.