Title
Human inference beyond syllogisms: an approach using external graphical representations.
Abstract
Research in psychology about reasoning has often been restricted to relatively inexpressive statements involving quantifiers (e.g. syllogisms). This is limited to situations that typically do not arise in practical settings, like ontology engineering. In order to provide an analysis of inference, we focus on reasoning tasks presented in external graphic representations where statements correspond to those involving multiple quantifiers and unary and binary relations. Our experiment measured participants' performance when reasoning with two notations. The first notation used topological constraints to convey information via node-link diagrams (i.e. graphs). The second used topological and spatial constraints to convey information (Euler diagrams with additional graph-like syntax). We found that topo-spatial representations were more effective for inferences than topological representations alone. Reasoning with statements involving multiple quantifiers was harder than reasoning with single quantifiers in topological representations, but not in topo-spatial representations. These findings are compared to those in sentential reasoning tasks.
Year
DOI
Venue
2019
10.1007/s10339-018-0877-2
Cognitive processing
Keywords
Field
DocType
Binary predicates,Diagrammatic reasoning,External representation,Inference,Quantifiers
Syllogism,Ontology engineering,Notation,Unary operation,Diagrammatic reasoning,Binary relation,Inference,Euler diagram,Cognitive psychology,Psychology,Natural language processing,Artificial intelligence
Journal
Volume
Issue
ISSN
20.0
1.0
1612-4790
Citations 
PageRank 
References 
0
0.34
18
Authors
4
Name
Order
Citations
PageRank
Yuri Sato1234.71
Gem Stapleton248256.25
Mateja Jamnik315830.79
Zohreh Shams410.69