Publikation: Evaluation of Cognitive Architectures Inspired by Cognitive Biases
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
Cognitive architectures are frequently built to model naturally intelligent behavior. This aims on two primary goals: On one hand these architectures model human behavior in order to give a better understanding of the human thought process. On the other hand cognitive architectures are an approach of modeling artificial intelligence. Those two goals might be conflicting, as humans sometimes act irrationally e.g. because they were cognitively biased. In this work, we analyze on a theoretical level whether cognitive architectures are also biased. Therefore we first abstract more general behavior from cognitive fallacies. Then we evaluate for the architectures Clarion, Leabra and Lida to what extent they can be biased.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
DOELL, Christoph, Sophie SIEBERT, 2016. Evaluation of Cognitive Architectures Inspired by Cognitive Biases. In: Procedia Computer Science. 2016, 88, pp. 155-162. eISSN 1877-0509. Available under: doi: 10.1016/j.procs.2016.07.419BibTex
@article{Doell2016Evalu-44682, year={2016}, doi={10.1016/j.procs.2016.07.419}, title={Evaluation of Cognitive Architectures Inspired by Cognitive Biases}, volume={88}, journal={Procedia Computer Science}, pages={155--162}, author={Doell, Christoph and Siebert, Sophie} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/44682"> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-01-23T11:18:35Z</dc:date> <dc:creator>Doell, Christoph</dc:creator> <dcterms:title>Evaluation of Cognitive Architectures Inspired by Cognitive Biases</dcterms:title> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/44682"/> <dc:creator>Siebert, Sophie</dc:creator> <dcterms:issued>2016</dcterms:issued> <foaf:homepage rdf:resource="http://localhost:8080/"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:abstract xml:lang="eng">Cognitive architectures are frequently built to model naturally intelligent behavior. This aims on two primary goals: On one hand these architectures model human behavior in order to give a better understanding of the human thought process. On the other hand cognitive architectures are an approach of modeling artificial intelligence. Those two goals might be conflicting, as humans sometimes act irrationally e.g. because they were cognitively biased. In this work, we analyze on a theoretical level whether cognitive architectures are also biased. Therefore we first abstract more general behavior from cognitive fallacies. Then we evaluate for the architectures Clarion, Leabra and Lida to what extent they can be biased.</dcterms:abstract> <dc:contributor>Doell, Christoph</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:language>eng</dc:language> <dc:contributor>Siebert, Sophie</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-01-23T11:18:35Z</dcterms:available> </rdf:Description> </rdf:RDF>