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.

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

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.

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.

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

Marchant, N., & Chaigneau, S. E. (2020). Modulating coherence effect in causal-based pro- cessing. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.

Marchant, N., & Chaigneau, S. E. (2020). Modulating coherence effect in causal-based processing. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.

Continuar leyendoMarchant, N., & Chaigneau, S. E. (2020). Modulating coherence effect in causal-based pro- cessing. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.

Académico PUCV lidera investigación que utiliza inteligencia artificial para comprender el razonamiento humano

Comprender por qué las personas cometen errores al razonar bajo incerteza es el objetivo de una investigación liderada por el Dr. Nicolás Marchant, académico de la Escuela de Psicología de la Pontificia Universidad Católica de Valparaíso (PUCV).

Continuar leyendoAcadémico PUCV lidera investigación que utiliza inteligencia artificial para comprender el razonamiento humano