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Enregistrement W2765305673

The Geometrician: a Computer Prototype of Problem Solving in Geometry Construction

2006· article· en· W2765305673 sur OpenAlexaffabout
Edgar R. Acosta Villasenor, Rafael Pérez y Pérez

Notice bibliographique

RevueProceedings of the Annual Meeting of the Cognitive Science Society · 2006
Typearticle
Langueen
DomainePsychology
ThématiqueCreativity in Education and Neuroscience
Établissements canadiensCarleton University
Organismes subventionnairesnon disponible
Mots-clésCreativityComputer scienceReflection (computer programming)Set (abstract data type)CompassComputer graphics (images)Artificial intelligenceGeometryArithmeticMathematicsProgramming languagePsychology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The Geometrician: a Computer Prototype of Problem Solving in Geometry Construction Edgar R. Acosta Villase˜ nor (avillase@connect.carleton.ca) Institute of Cognitive Science; 1125 Colonel By Drive Ottawa, ON K1S 5B6 Canada Rafael P´ erez y P´ erez (rpyp@servidor.unam.mx) Instituto de Investigaci´on en Matem´aticas Aplicadas y en Sistemas UNAM, Mexico, DF 04510 Mexico Keywords: creativity; problem solving; geometry. Introduction Most theories of creativity assume the interaction of two kinds of cognitive processes: the generation and evalua- tion of possible ideas (Sternberg & Lubart, 1999). P´erez y P´erez and Sharples (2001) described in great detail both processes in their Engagement-Reflection computer model of creativity (E&R model). Originally the model was developed with the aim of describing in detail a cog- nitive account of creative writing. As a way to improve the model, and to evaluate its potential for problem solving, a computer program based on the E&R model known as the Geometrician was implemented. The Geometrician The Geometrician solves geometry construction prob- lems in which, given some initial geometric objects (e. g. points, lines), new geometric objects are constructed employing only a straightedge and a compass. The E&R model, and its implementation in the Geometrician are outlined in this document. Engagement & Reflection The E&R model establishes that all knowledge struc- tures in the system are created from a set of previous solved problems provided by the user. Once these struc- tures are created the system starts to solve the problem through a cycle between two processes: engagement and reflection. Engagement is the generative process in the E&R model. During engagement, the system employs the problem’s context as a cue to probe memory and re- trieve a set of possible actions to perform in order to solve the problem. After a number of actions are produced, or if the system is unable to retrieve more actions from memory (i. e. if an impasse is declared), the reflection process takes control. During reflection, the system evaluates the actions generated so far and eliminates those that are not use- ful to solve the problem, checks the coherence of the sequence of actions generated during engagement, tries to break impasses, determines whether the problem has been solved, and generates a set of guidelines that drive the production of material during engagement. Then the system switches back to engagement. In this way, the outputs of the system are the result of the interaction between engagement and reflection. The cycle ends when the problem is solved or when it is impossible to break an impasse. Each time a problem is solved, the solution is added to the system’s knowledge base. Implementation The actual implementation of the Geometrician does not embody the whole E&R model (e. g. the func- tion to eliminate useless actions has not been finished yet). However, the Geometrician contributes with some characteristics not present in the original E&R model, as for example the capacity to execute the E&R cycle recursively to solve sub-problems of the current prob- lem. A sub-problem is created each time the sequence of produced actions lacks coherence. Discussion The prototype provides some insights on how useful the E&R model is for problem solving in geometry. In an ex- periment the Geometrician was provided with an initial knowledge base consisting of 3 solved problems. With this information the system was able to solve four new and more complex problems. Another interesting feature of the model is that dif- ferent solutions were produced on different runs. This occurred because the search on memory could retrieve more than one candidate action, and the engagement procedure selected only one. Thus, the decisions made by the system influenced the way in which the problem was solved. Conclusion Although the Geometrician is just a prototype subject to further development, the interaction between the en- gagement and reflection procedures proved to be useful on problem solving. References P´erez y P´erez, R., & Sharples, M. (2001). Mexica: A computer model of a cognitive account of creative writ- ing. J. Expt. Theor. Artif. Intell., 13, 119–139. Sternberg, R. J., & Lubart, T. I. (1999). The concept of creativity: Prospects and paradigms. In R. J. Stern- berg (Ed.), Handbook of creativity. Cambridge Univer- sity Press.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,041
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,004
Études des sciences et des technologies0,0010,004
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,294
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2006
Routes d'admission2
Résumé présentoui

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