Symposium: Creative Cognition - eScholarship
Notice bibliographique
Résumé
Symposium: Creative Cognition Will Bridewell (will.bridewell@nrl.navy.mil) Navy Center for Applied Research in Artificial Intelligence Washington, DC 20375 USA Liane Gabora (liane.gabora@ubc.ca) Department of Psychology, University of British Columbia Kelowna BC V1V 1V7 Canada David Kirsh (kirsh@ucsd.edu) Department of Cognitive Science, University of California La Jolla, CA 92093 USA Paul Thagard (pthagard@uwaterloo.ca) Department of Philosophy, University of Waterloo Waterloo, ON N2L 3G1 Canada Keywords: Creativity, cognitive processes, domains, learning, adaptation, methods. provided hard constraints not only on the form of the constructed models but also on the space of potential solutions, calling any attribution of creativity into question. However, recent versions possess the capacity to learn knowledge from their modeling experiences. This knowledge improves their ability to account for data in later tasks. In this context, he will identify how such systems can violate their own constraints to create models by exploring outside-the-box solutions. Introduction Creativity is the generation of products and ideas that are new, valuable, and surprising. Interdisciplinary research in cognitive science makes it clear that creativity does not have to be the mysterious result of divine inspiration. Rather, we can investigate the mental processes that have creative results. This symposium will discuss creativity from a combination of disciplinary vantage points, including philosophy, psychology, neuroscience, and computer modeling. We will try to answer questions such as the following: What are the most important cognitive processes involved in producing creative results? Do these cognitive processes operate in the same way across the many domains of creativity, including science, technology, the arts, and social innovation? How can understanding of cognitive processes be used to enhance creativity? Is creativity amenable to computer modeling? Is there an optimal level of creativity at the individual and social level? Liane Gabora Liane Gabora, an Associate Professor of Psychology at the University of British Columbia, has over 130 publications on the mechanisms underlying creativity and the cultural evolution of creative ideas. She has lectured on creativity worldwide and secured funding for her research totaling over one million dollars from sources in Canada, Europe, and the USA. She will present a theory of creativity, honing theory, according to which the creative mind is a self-organizing, autopoietic structure, and the creative impulse stems from its self-mending tendencies. She will present converging evidence for honing theory from neuroscience, studies of painting and analogy formation, a mathematical theory of concepts that incorporates their contextual, non- compositional nature, and an agent-based computer model of the birth and evolution of ideas. In this computer model the cultural evolution of ideas is not open-ended unless agents can chain simple ideas into more complex ones. The adaptive value and diversity of new ideas increases when agents can (1) shift between convergent and divergent processing modes, or (2) adjust their ratio of inventing to imitating over time in accordance with the success of their creative ideas. She will show that individual creative styles are recognizable not just within a domain, but across domains (e.g., if we know someone’s writing style we are more likely than chance to know which artworks were Will Bridewell Will Bridewell earned his PhD in Computer Science in 2004 from the University of Pittsburgh, where he developed a simple method for detecting negation in medical records and a unique approach to explaining anomalies in scientific data. He then moved to Stanford University where he conducted research in computational scientific discovery and socially aware inference. In 2013, he joined the Naval Research Laboratory to investigate the interaction between attention and perception in cognition. For the symposium, he will discuss his research on computational systems that construct mathematical models from scientific data. The need for human-encoded knowledge limited the capabilities of early versions of these systems. More specifically, the rigidity of this knowledge
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».