Vanderbilt University 2006
Assistant Professor, Cognitive Science
Office Hours: Flexible, by appointment
Phone Number: (631) 632-7086
Areas of Interest: High-level cognition; causal and associative learning, probabilistic reasoning, economic and perceptual decision making, neuroimaging and computational modeling.
I am interested in how people make decisions in the face of incomplete, inconsistent, ambiguous, or uncertain information. I am exploring this interest in a variety of domains. Utilizing behavioral and computational methods, my work in the area of learning suggests that learners are adept at dealing with incomplete data, a situation ignored by current learning theories. Utilizing functional magnetic resonance imaging, my work in economic decision-making explores the neural bases of decision-makers' ability to foresee, evaluate, and react to the presence of uncertainty. My behavioral work on perceptual decision-making explores both how even relatively simple decisions involve integrating noisy information over time and how decision-makers evaluate quantities such as confidence.
Luhmann, C. C., & Ahn, W. (2007). BUCKLE: A model of unobserved cause learning, Psychological Review, 114, 657-677.
Ahn, W., Marsh, J. K., & Luhmann, C. C. (2007). Dynamic interpretations of covariation data. In Gopnik, A., & Schultz, L. (Eds.), Causal learning: Psychology, philosophy, and computation. Oxford: Oxford University Press.
Luhmann, C. C., Ahn, W., & Palmeri, T. J. (2006). Theory-based categorization under speeded conditions, Memory & Cognition, 34, 1102-1111.
Luhmann, C. C., & Ahn, W.(2006). Modeling the role of unobserved causes in causal learning. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1741-1746). Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc.
Luhmann, C. C., & Ahn, W. (2005). The meaning and computation of causal power: A critique of Cheng (1997) and Novick and Cheng (2004). Psychological Review, 112, 685-692.
Luhmann, C. C. (2005). Confounded: Causal inference and the requirement of independence. In B. G. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the 27th Annual Conference of the Cognitive Science Society (pp. 1355-1360). Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc.
Ahn, W., & Luhmann, C. C. (2005). Demystifying theory-based categorization. In L. Gershkoff-Stowe & D. Rakison (Eds.) Building object categories in developmental time (277-300). Mahwah, New Jersey: Lawrence Earlbaum Associates, Inc.
Luhmann, C. C. & Ahn, W. (2003). Evaluating the causal role of unobserved variables. In R. Alterman & D. Kirsh (Eds.), Proceedings of the 25th Annual Conference of the Cognitive Science Society (734-739). Mahwah, New Jersey: Lawrence Earlbaum Associates, Inc.
Luhmann, C. C., Ahn, W., & Palmeri, T. J. (2002). Theories and similarity: Categorization under speeded conditions. In W. D. Gray & C. D. Schunn (Eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society (590-595). Mahwah, New Jersey: Lawrence Earlbaum Associates, Inc.
Ahn, W., Marsh, J., Luhmann, C. C., & Lee, K (2002). Effect of theory-based feature correlations on typicality judgments. Memory & Cognition, 30, 107-118.
Ahn, W., Kalish, C., Gelman, S. A., Medin, D. L., Luhmann, C., Atran, S., Coley, J. D., Shafto, P. (2001). Why essences are essential in the psychology of concepts. Cognition, 82, 59-69.