Notice bibliographique
Résumé
This research is an exploration of the phenomenon of "intuition" in the context of artificial intelligence (AI). In this work, intuition was considered as the human capacity to make decisions under situations in which the available knowledge was usually low in quality: inconsistent and of varying levels of certainty. The objectives of this study were to characterize some of the aspects of human intuitive thought and to model these aspects in a computational approach. This project entailed the development of a conceptual framework and a conceptual model, and, based on these, a computer system with three general parts: (1) a rule induction module for establishing the knowledge base for the reasoner; (2) the intuitive reasoner that was essentially a rule-based inference engine; (3) two learning approaches that could update the knowledge base over time for the reasoner to make better predictions. A reference reasoner based on established data analysis methods was also constructed, as a bench-mark for evaluating the intuitive reasoner. The input and the rules drawn by the reasoner were allowed to be fuzzy, multi-valued, and of varying levels of certainty. A measure of the certainty level, Strength of Belief, was attached to each input as well as each rule. Rules for the intuitive reasoner were induced from only about 10% of the data available for the reference reasoner. Solutions were formulated through iterations of consolidating intermediate reasoning results, during which the Strength of Belief of corroborating intermediate results was combined. The intuitive and the reference reasoners were tested to predict the value (class) of 12 target variables chosen by the author, of which six were continuous variables and the other six were discrete variables. The intuitive reasoner developed in this study matched the performance of the reference reasoner for three of six continuous target variables and achieved at least 70% of the accuracy of the reference reasoner for all six discrete target variables. The results showed that the intuitive reasoner was able to induce rules from a sparse database and use those rules to make accurate predictions. This suggested that by consolidating numerous outputs from low-certainty rules, an "intuitive" reasoner can effectively perform prediction, or other computational tasks, on the basis of incomplete information of varying quality.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».