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Marchant, N., Quillien, T., & Chaigneau, S. E. (2023). A context-dependent Bayesian account for causal-based categorization. Cognitive Science, 47(1).

Marchant, N., Quillien, T., & Chaigneau, S. E. (2023). A context-dependent Bayesian account for causal-based categorization. Cognitive Science, 47(1).

Continuar leyendoMarchant, N., Quillien, T., & Chaigneau, S. E. (2023). A context-dependent Bayesian account for causal-based categorization. Cognitive Science, 47(1).
Lee más sobre el artículo Marchant, N., & Chaigneau, S. E. (2022). On the importance of feedback for categorization: Re- visiting category learning experiments using an Adaptive Filter model. Journal of Experimental Psychology: Animal Learning & Cognition, 48(4), 295-306.

Marchant, N., & Chaigneau, S. E. (2022). On the importance of feedback for categorization: Re- visiting category learning experiments using an Adaptive Filter model. Journal of Experimental Psychology: Animal Learning & Cognition, 48(4), 295-306.

Marchant, N., & Chaigneau, S. E. (2022). On the importance of feedback for categorization: Revisiting category learning experiments using an Adaptive Filter model. Journal of Experimental Psychology: Animal Learning &…

Continuar leyendoMarchant, N., & Chaigneau, S. E. (2022). On the importance of feedback for categorization: Re- visiting category learning experiments using an Adaptive Filter model. Journal of Experimental Psychology: Animal Learning & Cognition, 48(4), 295-306.
Lee más sobre el artículo Marchant, N., Zhao, B., Bramley, N. R., Morales, D., & Chaigneau, S. E. (2022). Categorizing perceived causal events. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.

Marchant, N., Zhao, B., Bramley, N. R., Morales, D., & Chaigneau, S. E. (2022). Categorizing perceived causal events. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.

Marchant, N., Zhao, B., Bramley, N. R., Morales, D., & Chaigneau, S. E. (2022). Categorizing perceived causal events. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.

Continuar leyendoMarchant, N., Zhao, B., Bramley, N. R., Morales, D., & Chaigneau, S. E. (2022). Categorizing perceived causal events. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.
Lee más sobre el artículo Marchant, N., & Chaigneau, S. E. (2022). Computational Cognitive models of Categorization: Predictions under conditions of classification uncertainty. Psykhe.

Marchant, N., & Chaigneau, S. E. (2022). Computational Cognitive models of Categorization: Predictions under conditions of classification uncertainty. Psykhe.

Marchant, N., & Chaigneau, S. E. (2022). Computational Cognitive models of Categorization: Predictions under conditions of classification uncertainty. Psykhe.

Continuar leyendoMarchant, N., & Chaigneau, S. E. (2022). Computational Cognitive models of Categorization: Predictions under conditions of classification uncertainty. Psykhe.
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Continuar leyendoMarchant, N., Canessa, E., & Chaigneau, S. E. (2022). An Adaptive Linear Filter model of procedural category learning. Cognitive Processing. – Duplicado – [#14089]
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Coinvestigador del proyecto Fondecyt Regular N°1260939 (2026-2029), Posterior Uncertainty and Human Probabilistic Inference.

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ANID Fondecyt Iniciación. Conociendo las causas de las fallas sistemáticas en el ra- zonamiento causal mediante la comparación de modelos computacionales cognitivos. N° 11250063.

Investigador responsable del Proyecto ANID Fondecyt Iniciación. Conociendo las causas de las fallas sistemáticas en el razonamiento causal mediante la comparación de modelos computacionales cognitivos. N° 11250063.

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Lee más sobre el artículo Marchant, N., Canessa, E., & Chaigneau, S. E. (2022). An Adaptive Linear Filter model of procedural category learning. Cognitive Processing.

Marchant, N., Canessa, E., & Chaigneau, S. E. (2022). An Adaptive Linear Filter model of procedural category learning. Cognitive Processing.

Marchant, N., Canessa, E., & Chaigneau, S. E. (2022). An Adaptive Linear Filter model of procedural category learning. Cognitive Processing.

Continuar leyendoMarchant, N., Canessa, E., & Chaigneau, S. E. (2022). An Adaptive Linear Filter model of procedural category learning. Cognitive Processing.
Lee más sobre el artículo Canessa, E., Chaigneau, S. E., & Marchant, N. (2023). Use of Agent-Based Modeling (ABM) in Psychological Research. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges in Cognitive Modeling. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health.

Canessa, E., Chaigneau, S. E., & Marchant, N. (2023). Use of Agent-Based Modeling (ABM) in Psychological Research. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges in Cognitive Modeling. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health.

Canessa, E., Chaigneau, S. E., & Marchant, N. (2023). Use of Agent-Based Modeling (ABM) in Psychological Research. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges…

Continuar leyendoCanessa, E., Chaigneau, S. E., & Marchant, N. (2023). Use of Agent-Based Modeling (ABM) in Psychological Research. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges in Cognitive Modeling. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health.
Lee más sobre el artículo Marchant, N., Canessa, E., & Chaigneau, S. E. (2023). Challenges from Probabilistic Learning for Models of Brain and Behavior. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges in Cognitive Modeling. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Springer, Cham.DOI: 10.1007/978-3-031-41862-46

Marchant, N., Canessa, E., & Chaigneau, S. E. (2023). Challenges from Probabilistic Learning for Models of Brain and Behavior. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges in Cognitive Modeling. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Springer, Cham.DOI: 10.1007/978-3-031-41862-46

Marchant, N., Canessa, E., & Chaigneau, S. E. (2023). Challenges from Probabilistic Learning for Models of Brain and Behavior. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends…

Continuar leyendoMarchant, N., Canessa, E., & Chaigneau, S. E. (2023). Challenges from Probabilistic Learning for Models of Brain and Behavior. In: Veloz, T., Khrennikov, A., Toni, B., Castillo, R.D. (eds) Trends and Challenges in Cognitive Modeling. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Springer, Cham.DOI: 10.1007/978-3-031-41862-46